Lead Quality Automation Engineer

Forward Deployed AI Strategist

Principal AWS Network Infrastructure Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Senior DevOps Engineer

QA Tester

Consulting Principal AWS Cloud Engineer

Testing

Role Description: <ul><li>We are seeking an experienced Lead Quality Automation Engineer to join our growing Quality Engineering practice in Leeds.&nbsp;</li><li>This role is suited to a highly technical Quality Engineer who enjoys solving complex engineering challenges while working directly with clients across multiple industries.&nbsp;</li><li>You will play a key role in designing automation solutions, driving engineering best practices, mentoring team members, and helping organisations modernise their quality engineering capabilities.&nbsp;</li><li>As a Lead Quality Automation Engineer, you will remain hands-on with automation development while providing technical leadership across delivery teams.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Design, develop and maintain scalable automated testing frameworks for enterprise applications.&nbsp;&nbsp;</li><li>Deliver high-quality automation solutions using modern testing tools and object-oriented programming languages.&nbsp;&nbsp;</li><li>Work collaboratively with software engineers, architects, product owners, and business stakeholders throughout the software development lifecycle.&nbsp;&nbsp;</li><li>Champion Shift-Left Quality Engineering practices by embedding testing early in the development process.&nbsp;&nbsp;</li><li>Analyse application source code to identify defects, improve test coverage, and support overall software quality.&nbsp;&nbsp;</li><li>Contribute to Continuous Integration and Continuous Delivery (CI/CD) pipelines to enable efficient automated testing.&nbsp;&nbsp;</li><li>Apply AI-assisted engineering tools and Generative AI technologies to improve testing efficiency and engineering productivity.&nbsp;&nbsp;</li><li>Provide technical leadership, mentoring, and guidance to junior engineers and project teams.&nbsp;&nbsp;</li><li>Support clients in adopting modern Quality Engineering practices and continuous improvement initiatives.&nbsp;&nbsp;</li><li>Participate in technical discussions, solution design, and engineering governance activities.&nbsp;&nbsp;</li></ul> Requirements: <ul><li>Proven experience in Quality Engineering and Test Automation within enterprise environments.&nbsp;&nbsp;</li><li>Hands-on experience developing and maintaining automation frameworks.&nbsp;&nbsp;</li><li>Strong programming experience in one or more object-oriented languages such as Java, Python, C#, JavaScript, or TypeScript.&nbsp;&nbsp;</li><li>Experience with modern automation frameworks such as Playwright, Selenium, or equivalent.&nbsp;&nbsp;</li><li>Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform.&nbsp;&nbsp;</li><li>Good understanding of Continuous Integration and Continuous Delivery (CI/CD) principles.&nbsp;&nbsp;</li><li>Experience working with AI productivity tools such as GitHub Copilot, Claude, or similar technologies.&nbsp;&nbsp;</li><li>Strong understanding of software development lifecycle (SDLC) and Shift-Left Testing methodologies.&nbsp;&nbsp;</li><li>Excellent communication and stakeholder management skills with the ability to work directly with clients.&nbsp;&nbsp;</li><li>Demonstrated ability to work independently while managing multiple priorities.&nbsp;&nbsp;</li></ul> Preferred Qualifications&nbsp; <ul><li>Commercial experience implementing Generative AI solutions within Quality Engineering.&nbsp;&nbsp;</li><li>Experience working within consulting or professional services organisations.&nbsp;&nbsp;</li><li>Knowledge of Agentic AI concepts.&nbsp;&nbsp;</li><li>Familiarity with LangChain and LangGraph.&nbsp;&nbsp;</li><li>Experience mentoring engineers and providing technical leadership.&nbsp;&nbsp;</li><li>Exposure to both public and private sector projects.&nbsp;&nbsp;</li></ul> Personal Attributes&nbsp; The successful candidate will demonstrate:&nbsp; <ul><li>Strong analytical and problem-solving skills.&nbsp;&nbsp;</li><li>Excellent verbal and written communication abilities.&nbsp;&nbsp;</li><li>Adaptability in fast-paced consulting environments.&nbsp;&nbsp;</li><li>A continuous learning mindset with evidence of ongoing professional development.&nbsp;&nbsp;</li><li>A collaborative approach with the ability to influence technical and non-technical stakeholders.&nbsp;&nbsp;</li></ul> Working Arrangement&nbsp; <ul><li>This role follows a hybrid working model with an expectation of approximately two to three days per week onsite, depending on client requirements.&nbsp;</li><li>Some travel to client locations may be required.&nbsp;</li></ul> Security Requirements&nbsp; <ul><li>Candidates must either hold Security Clearance (SC) or be eligible to obtain SC Clearance in accordance with UK Government requirements.&nbsp;</li></ul>

Role Description: <ul><li>The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.</li><li>The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact.&nbsp;</li><li>The individual is expected to work in close partnership with our client IT team, to leverage existing AI &amp; data capabilities on Databricks &amp; AWS (where applicable) while developing solutions.</li></ul> Responsibilities: Strategic problem solving and driving cross-functional execution&nbsp; <ul><li>Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation</li><li>Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&amp;L owners</li><li>Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace</li></ul> Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions&nbsp; <ul><li>Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)</li><li>Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes</li></ul> Executing rapid AI-augmented research and competitive intelligence&nbsp; <ul><li>Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights</li><li>Synthesize structured datasets (S&amp;P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs</li></ul> Support strategy team in day-to-day execution by leveraging AI-led tools <ul><li>Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling</li><li>Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&amp;Ls, pricing</li><li>Support M&amp;A pipeline by AI-screening targets and generating investment theses</li></ul> AI enablement, coaching and continuous innovation <ul><li>Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution</li><li>Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users</li><li>Stay current on agentic stacks, multimodal models, and deep research agents</li></ul> Requirements: Skillset and capabilities AI fluency and hands-on deployment orientation&nbsp; <ul><li>Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.</li><li>Proven ability to convert business problems into reusable AI workflows, tools, or accelerators</li><li>Builder mindset with experience prototyping AI solutions using frontier tools &amp; low-code platforms</li></ul> Analytics, modelling, and research excellence <ul><li>Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.</li><li>Ability to synthesize structured datasets with unstructured sources</li><li>Research discipline – source triangulation and rigorous validation of AI outputs</li></ul> Strategic problem solving, communication, executive presence, and influence&nbsp; <ul><li>Sharp "so-what" orientation to translate AI outputs into practical executive decisions</li><li>Crisp written and verbal communication, with ability to frame board-ready narratives</li><li>Skill in explaining AI workflows and implications to both technical and non-technical audiences</li><li>Stakeholder management across strategy, commercial, data, and technology teams</li></ul> Ownership, and execution <ul><li>Independently own workstreams end-to-end – from framing through deployment</li><li>High bar for quality; never publishes unchecked AI outputs or unvalidated analysis</li></ul> Coaching and capability building&nbsp; <ul><li>Patience and ability to coach colleagues on prompting, research workflows, and source validation</li><li>Track record of building reusable playbooks – templates and training modules that scale adoption</li></ul> Passion, curiosity, and learning agility <ul><li>Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools</li><li>Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability</li></ul> Qualifications:&nbsp; <ul><li>BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.</li><li>3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.</li><li>Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.</li><li>Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.</li><li>Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.</li><li>Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.</li><li>Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.</li><li>Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage</li></ul>

Responsibilities: Design and Implementation:&nbsp; <ul><li>Architect and deploy scalable, secure, and highly available network infrastructure solutions in AWS</li></ul> Network Management:&nbsp; <ul><li>Manage and optimize AWS networking services such as VPC, Direct Connect, Route 53, CloudWAN, and Transit Gateway</li></ul> Security:&nbsp; <ul><li>Implement and maintain network security best practices, including firewalls, VPNs, and security groups</li></ul> Automation:&nbsp; <ul><li>Develop and maintain automation scripts using tools like Terraform, CloudFormation, and Python</li></ul> Monitoring and Troubleshooting:&nbsp; <ul><li>Monitor network performance and troubleshoot issues to ensure optimal performance and reliability</li></ul> Collaboration:&nbsp; <ul><li>Work with cross-functional teams to support application development and deployment</li></ul> Documentation:&nbsp; <ul><li>Create and maintain detailed network documentation and diagrams</li></ul> Cost Management:&nbsp; <ul><li>Monitor and optimize cloud costs, implementing cost-saving measures where possible</li></ul> Compliance and Governance:&nbsp; <ul><li>Ensure that all cloud network solutions comply with our client standards</li></ul> Performance Tuning:&nbsp; <ul><li>Continuously improve the performance and reliability of network systems</li></ul> Incident Response:&nbsp; <ul><li>Lead incident response efforts for network-related issues and outages</li></ul> Training and Mentorship:&nbsp; <ul><li>Provide training and mentorship to junior network engineers and other team members</li></ul> Innovation/Continuous Learning:&nbsp; <ul><li>Stay updated with the latest cloud networking technologies and propose innovative solutions to improve the infrastructure</li></ul> Business Competencies: <ul><li class="ql-indent-1">Adaptable to work effectively within a variety of situations and with various individuals, groups or independently</li><li class="ql-indent-1">Ability to document and communicate effectively, explaining technical concepts and network initiatives in business terms in both individual and group settings</li><li class="ql-indent-1">Must be tenacious, overcoming obstacles and identifying risks</li><li class="ql-indent-1">Attention to detail will be critical to assist with the successful implementation of initiatives</li></ul> Requirements: <ul><li class="ql-indent-1">10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li class="ql-indent-1">Strong understanding of AWS network infrastructure and service integration, including VPC, IAM, Transit Gateway, and CloudFormation, and how AWS services such as EC2, EKS, RDS, S3, and Lambda operate within those network architectures.</li><li class="ql-indent-1">Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).</li><li class="ql-indent-1">Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).</li></ul> Technical Skills: <ul><li class="ql-indent-1">In-depth knowledge of AWS networking services and best practices, such as VPC, AWS Firewall, Transit Gateway, WAF, Security Groups, CloudWAN, NACLS, Shield Advance, and Direct Connect</li><li class="ql-indent-1">Advanced understanding of networking protocols and services such as BGP, OSPF, TCP/IP, DNS, DHCP, and VPNs</li><li class="ql-indent-1">Proficiency in network security principles and tools</li><li class="ql-indent-1">Skilled in network automation and scripting</li><li class="ql-indent-1">Experience in developing IaC with advanced skills in tools such as Terraform, AWS CloudFormation, and Ansible for automating infrastructure deployment and management</li><li class="ql-indent-1">Familiar with DevOps practices / CI/CD pipelines using tools like Jenkins, GitLab CI, or GitHub Actions to automate testing and deployment</li></ul>&nbsp;

Role Description: <ul><li>Working closely with the Data Scientists and be responsible for implementing large language models (LLMs) based applications, working with proprietary and open-source Models as well as popular frameworks such as Lang Chain to ensure seamless integration and deployment.</li></ul> Responsibilities: <ul><li>Building standalone applications that interact with LLM models.</li><li>Building RAG-based applications.</li><li>Understanding of Vector DBs like Solr for LLM based applications</li><li>Integrate models with existing systems and APIs.</li><li>Implement production quality ETL jobs</li><li>Preprocess and manage data for training and deployment.</li><li>Collaborate with cross-functional teams to define, design, and ship new features.</li><li>Write clean, maintainable, and efficient code.</li><li>Document development processes, code, and APIs.</li></ul> Requirements: <ul><li>Degree in Computer Science, Data Science, or related field.• Proven experience in building customer facing ML based APIs</li><li>Mexico City–based (or nearby), available to work onsite 2 days per week at Glorietadel Ahuehuete, Reforma.</li><li>Experience in developing applications that are scalable to handle TBs of data</li><li>Strong knowledge of API integration (RESTful, GraphQL).</li><li>Experience with data preprocessing, SQL, and NoSQL databases as well as vector stores (e.g., Postgres, MySQL, Solr, Elasticsearch/OpenSearch, etc.).</li><li>Familiarity with deployment tools (Docker, Kubernetes).</li><li>Experience with DevOps tools like Jenkins, Terraform, Cloud Formation templates is highly preferred.</li><li>Excellent problem-solving and communication skills.</li><li>Experience with Spark/Hadoop, EMR or any other Big Data technology would be a plus</li><li>Experience working on agents is considered a good-to-have</li><li>Familiarity with agents, even through courses Work in a way that works for you We promote a healthy work/life balance across the organization..</li></ul> Other Information: These are some of the benefits we are delighted to offer: <ul><li>Private Medical/Dental Plan.</li><li>Savings Fund.</li><li>Life Insurance.</li><li>Meal/Grocery Voucher.</li><li>We offer an appealing working prospect for our people.</li><li>With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.</li><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working for you.</li><li>We know that your well-being and happiness are key to a long and successful career.</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: Cloud Infrastructure Design and Deployment: <ul><li>Architect, design, and implement scalable, reliable, and secure solutions on GCP.</li><li>Deploy and manage GCP services in both development and production environments, ensuring seamless integration with existing infrastructure.</li><li>Implement and manage core services such as BigQuery, Datafusion, Cloud Composer (Airflow), Cloud Storage, Data Fusion, Compute Engine, App Engine, Cloud Functions and more.</li></ul> Infrastructure as Code (IaC) and Automation: <ul><li>Develop and maintain infrastructure as code using Terraform or CLI scripts to automate provisioning and configuration of GCP resources.</li><li>Establish and document best practices for IaC to ensure consistent and efficient deployments across environments.</li></ul> DevOps and CI/CD Pipeline Development: <ul><li>Create and manage DevOps pipelines for automated build, test, and release management, integrating with tools such as Jenkins, GitLab CI/CD, or equivalent.</li><li>Work with development and operations teams to optimize deployment workflows, manage application dependencies, and improve delivery speed.</li></ul> Security and IAM Management: <ul><li>Handle user and service account management in Google Cloud IAM.</li><li>Set up and manage Secrets Manager and Cloud Key Management for secure storage of credentials and sensitive information.</li><li>Implement network and data security best practices to ensure compliance and security of cloud resources.</li></ul> Performance Monitoring and Optimization: <ul><li>Monitoring &amp; Security: Set up observability tools like Prometheus, Grafana, and integrate security tools (e.g., SonarQube, Trivy).</li><li>Networking &amp; Storage: Configure DNS, networking, and persistent storage solutions in Kubernetes.</li><li>Set up monitoring and logging (e.g., Cloud Monitoring, Cloud Logging, Error Reporting) to ensure systems perform optimally.</li><li>Troubleshoot and resolve issues related to cloud services and infrastructure as they arise.</li></ul> Workflow Orchestration: <ul><li>Orchestrate complex workflows using Argo Workflow Engine.</li><li>Containerization: Work extensively with Docker for containerization and image management.</li><li>Optimization: Troubleshoot and optimize containerized applications for performance and security.</li></ul> Requirements:﻿ <ul><li>Bachelors or masters degree in computer science, Information Technology, or a similar field</li><li>Must have 10 + years of extensive experience in designing, implementing, and maintaining applications on GCP and OpenShift</li><li>Comprehensive expertise in GCP services such as GKE, Cloudrun, Functions, Cloud SQL, Firestore, Firebase, Apigee, GCP App Engine, Gemini Code Assist, Vertex AI, Spanner, Memorystore, Service Mesh, and Cloud Monitoring</li><li>Solid understanding of cloud security best practices and experience in implementing security controls in GCP</li><li>Thorough understanding of cloud architecture principles and best practices</li><li>Experience with automation and configuration management tools like Terraform and a sound understanding of DevOps principles</li><li>Proven leadership skills and the ability to mentor and guide a technical team</li></ul>

Responsibilities: <ul><li>Develop detailed test plans based on project requirements and specifications.&nbsp;</li><li>Provide feedback on quality standards, usability, and areas for improvement.</li><li>Automates test scenarios and expected outcomes.&nbsp;</li><li>Conduct regression, integration, user acceptance, and performance testing.</li><li>Conducts comprehensive testing and risk-based assessments of the testing objects.&nbsp;</li><li>He/She uses source documentation as input and contributes to the planning and implementation of testing activities.&nbsp;</li><li>Leads testing components of large and complex projects, assigns tasks, provides direction to resources, and reports progress to project stakeholders.&nbsp;</li><li>He/She creates and selects tools and methodologies for review and approval by management.</li></ul> ﻿Requirements: <ul><li>Bachelors Degree or International equivalent&nbsp;</li><li>Bachelors Degree or International equivalent in Computer Science, Information Systems, Mathematics, Statistics or related field - Preferred&nbsp;</li><li>comprehensive knowledge of technical skills, principles, practices, and procedures of testing methodologies and working knowledge in planning, designing, and conducting QA reviews and inspections.&nbsp;</li><li>He/She provides expertise for key business functions and supporting technologies.&nbsp;</li><li>Provides mentorship and expertise in technologies and processes for Information Services Management (ISM) and Quality Assurance (QA).&nbsp;</li><li>He/She maintains an awareness of emerging technologies to ensure a competitive advantage.</li><li>Experience with both web and client/server based testing</li><li>Minimum 8 Years of Relevant Experience in IT Test Automation.</li><li>Should have strong Mainframe testing [CICS, JCL, DB2, Cobol]</li><li>Must be able to test and debug batch jobs (JCL).</li><li>Must be able to perform backend testing by executing SQL queries.</li><li>Expertise in APIs &amp; Web Services testing</li><li>Hands-on experience in Selenium, TestNG and Cucumber frameworks</li><li>Good in test execution reporting skills</li><li>Expertise in Test Cases Design and Test Data management</li><li>Expertise in tools like PostMan, SOAP UI, WinSCP, Oracle, Jenkins, GitHub and AppDynamics.</li><li>Should be well versed with Agile testing and Continuous Testing</li><li>Experience with Test Management tools</li><li>Knowledge on AZURE DEVOPS&nbsp;</li><li>Understanding of SAFe Agile methodologies</li><li>Should be solution-oriented and have problem solving aptitude</li><li>Should have excellent communication and presentation skills</li><li>Knowledge on Logistics domain will be an advantage</li><li>Good to have Performance Testing experience.</li><li>Knowledge on JMeter / Performance center will be an advantage.</li><li>Any certifications in test automation</li></ul>

Responsibilities: <ul><li>Demonstrated ability to drive cultural change and advocate for cloud transformation Key Responsibilities Cloud Strategy &amp; Leadership&nbsp;</li><li>Develop and implement a comprehensive AWS cloud strategy, ensuring alignment with business and technology goals.&nbsp;</li><li>Provide technical leadership and advocacy, championing cloud-native best practices and innovation.&nbsp;</li><li>Lead and drive architectural decisions, ensuring scalability, security, and operational efficiency.</li><li>Cloud Architecture &amp; Design&nbsp;</li><li>Architect secure, scalable, and highly available AWS cloud environments.&nbsp;</li><li>Develop and maintain enterprise-wide cloud blueprints, patterns, and frameworks to drive consistency.&nbsp;</li><li>Research and integrate emerging cloud technologies to foster continuous innovation. Infrastructure as Code &amp; Automation&nbsp;</li><li>Lead adoption and implementation of Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, and Helm.&nbsp;</li><li>Design and optimize CI/CD pipelines to streamline cloud deployments and operations.&nbsp;</li><li>Implement self-healing and automated failover mechanisms to enhance resilience and reliability.</li><li>Kubernetes &amp; Cloud-Native Technologies&nbsp;</li><li>Manage and optimize Kubernetes clusters (EKS, Helm, IAM) for scalability and security.&nbsp;</li><li>Define and enforce best practices for containerized applications and orchestration.&nbsp;</li><li>Improve Kubernetes networking, ingress, and observability solutions to enhance performance. Security &amp; Compliance&nbsp;</li><li>Establish and enforce security best practices for AWS environments, including IAM, WAF, Secret Manager, and encryption.&nbsp;</li><li>Implement zero-trust security models and secure multi-account AWS environments.&nbsp;</li><li>Conduct security audits, incident response, and ensure compliance with industry standards. Monitoring, Logging &amp; Reliability Engineering.</li><li>Deploy and manage monitoring tools (DataDog, Splunk, CloudWatch, Coralogix) to ensure visibility and observability.&nbsp;</li><li>Implement SRE principles to enhance system uptime, reliability, and efficiency.&nbsp;</li><li>Conduct post-mortem analysis and drive continuous improvements in cloud performance. Collaboration &amp; Thought Leadership&nbsp;</li><li>Work closely with software developers, system engineers, and security teams to design and implement cloud solutions.&nbsp;</li><li>Provide mentorship, training, and technical leadership to engineering teams.&nbsp;</li></ul> Requirements: <ul><li>10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li>Deep understanding of AWS services, including EC2, EKS, RDS, S3, Lambda, VPC, IAM, Transit Gateway, and CloudFormation.&nbsp;</li><li>Expertise in Kubernetes (EKS, Helm, Daemon Sets, StatefulSets, Karpenter, external-dns, aws-cni).&nbsp;</li><li>Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).&nbsp;</li><li>Hands-on experience managing CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).&nbsp;</li><li>Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).&nbsp;</li><li>Strong networking and security knowledge (DNS, VPC, NAT, Security Groups, IAM).&nbsp;</li><li>Experience designing and developing scalable, production-grade software tools and automation scripts using Python. Preferred Certifications&nbsp;</li><li>AWS Certified Solutions Architect – Professional (or equivalent).&nbsp;</li><li>Additional certifications in Kubernetes (CKA), AWS Security, or DevOps are a plus. Leadership &amp; Soft Skills&nbsp;</li><li>Proven experience leading cloud architecture and strategy initiatives.&nbsp;</li><li>Ability to mentor and guide technical teams in a fast-paced, agile environment.&nbsp;</li><li>Strong problem-solving and troubleshooting skills in complex cloud environments.</li><li>Excellent communication skills with the ability to translate technical concepts for engineering, business, and executive stakeholders.&nbsp;</li></ul>

<h2>About the job</h2> About Tabsquare TabSquare provides AI-powered technology solutions for the F&amp;B industry. Through TabSquares solutions, restaurants can efficiently manage orders, process payments, and effectively engage with their customers. TabSquare assists partner restaurants in driving higher sales, streamlining operations, and delivering an enhanced customer experience. TabSquare is a market leader with operations in Singapore, Malaysia, Indonesia, Australia, the Philippines, Taiwan, Thailand, Hong Kong, Sweden, and the UAE. Trusted by thousands of restaurants, TabSquares clients include well-known F&amp;B brands such as Pizza Hut, KFC, Minor Food Group, Sushi Tei, Paradise Food Group, Japan Foods Holding, Zingrill Holdings, The Coffee Club, Old Town White Coffee, Secret Recipe, and many more. TabSquare is a wholly owned subsidiary of Delivery Hero, a global leader in the food delivery industry. For more information, visit <a href="http://www.tabsquare.ai/" rel="noopener noreferrer" target="_blank" style="color: var(--color-text);">http://www.tabsquare.ai</a> Responsibilities: <ul><li>Estimate, plan, prioritize and coordinate testing activities for the cross functional QA team.</li><li>Review requirements, specifications or design documents to provide timely and meaningful feedback</li><li>Create detailed, comprehensive, and well-structured documentations, test plans and test cases.</li><li>To perform system testing and end-user testing on our suite of solutions (end to end); comprising web-based applications, mobile apps on both Android and iOS platforms.</li><li>Track QA metrics, like defect densities and open defect counts and do updates on daily, weekly and monthly basis. </li><li>Design, develop and execute Automation Scripts using Katalon Studio / Selenium or similar tools.</li><li>Support and manage UAT, Sanity, Regression activities in multiple environments.</li><li>Monitor, debug and compare the system logs, error using Datadog in multiple environments.</li><li>Work closely with the stakeholders, engineering team and also the product team, to ensure the quality/stability of the software releases.</li><li>Research on new technologies or market trends, to be able to propose new solutions/features, recommendations or ideas to improve the software solution.</li><li>Adopts and improves all required QA Processes, SOP and Ground Rules as needed.</li><li>Perform other relevant duties as assigned by Head/Managers.</li></ul> The Employee, as per business needs, may be required to undertake any other such duties as may be assigned in line with the employee’s position, skills, and capabilities. Requirements: <ul><li>Bachelors degree in Computer Science / Application or related major.</li><li>Minimum 4-6 years of hands-on experience in Manual &amp; Automation Testing.</li><li>Excellent communication skills and a good command of English.</li><li>Self-motivated, detail-oriented, with strong analytical and problem solving skills. Able to work independently with minimum supervision.</li><li>Good understanding of the software development, testing &amp; bug life cycle process.</li><li>Strong technical experience and ability to automate tests using Java, JS or Python.</li><li>Technical experience with API’s, JSON, SQL, HTML and tools like Postman to check &amp; validate test results.</li><li>Technical experience with CI/CD tools like Jenkins, Gitlab and Load Test tools like Locust, JMeter.</li></ul> Tools / Technology: Selenium, Cucumber, Java, Rest Assured, Katalon, Appium, JMeter, Locust, TestRail, Datadog, PostMan, Sequel Pro, Slack, Atlassian.

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Lead Quality Automation Engineer

Forward Deployed AI Strategist

Principal AWS Network Infrastructure Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Senior DevOps Engineer

QA Tester

Consulting Principal AWS Cloud Engineer

Testing

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9 jenkins Jobs found

Lead Quality Automation Engineer

Forward Deployed AI Strategist

Principal AWS Network Infrastructure Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Senior DevOps Engineer

QA Tester

Consulting Principal AWS Cloud Engineer

Testing

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WhiteCrow is on a mission to connect companies with the best talent across the globe.