AVP, Principal Software Engineer (Front-End)

Software Engineer – Ag & Trade

VP, Engineering Manager

Senior IT Engineer

Lead Quality Automation Engineer

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

Lead Software Engineer, QA

Responsibilities: <ul><li>Lead development teams through all phases of the Agile development life cycle.</li><li>Coach and mentor junior talent, including pair-programming and reviewing AIgenerated code with engineering judgment.</li><li>Influence and collaborate with software developers, UX designers, product managers, application architects, and customer application experts to create</li><li>amazing apps.</li><li>Champion responsible adoption of AI coding assistants (GitHub Copilot, Claude Code, Cursor) on the team—setting prompt patterns, distinguishing AI Skills</li><li>(deterministic capabilities) from Agents (autonomous, multi-step workflows), and following company guidance for data handling, PII protection, IP compliance, and code provenance in regulated financial services contexts.</li><li>Ensure compliance with architecture, security, and technology standards set by company.</li><li>Participate in addressing root cause analyses, incident reports, and provide direction in problem resolution.</li><li>Ability to analyze production defects, troubleshoot systems, identify root cause, and implement fixes.</li><li>Provide 24x7 on-call support periodically throughout the year.</li><li>Identify ways to increase efficiency and improve system performance, including by piloting AI tools and agentic workflows for repetitive engineering tasks.</li><li>Work with third party vendors to develop software and/or integrate their software into company products.</li></ul> Requirements: <ul><li>Bachelor’s degree and a minimum of 5 years in full stack development with a strong focus on JavaScript (React JS in particular) OR, in lieu of degree, with 7 years of experience in the same.</li><li>Hands-on experience using at least one AI coding assistant (GitHub Copilot, Claude Code, Cursor, or equivalent) as part of regular development workflow.</li><li>Proficiency in TypeScript, JavaScript, React, Redux, Styled-Components, and RTL or Cypress.</li><li>Familiarity with AI-native concepts—RAG patterns, vector databases, MCP (Model Context Protocol), and agent orchestration—and how they differ from</li><li>traditional architecture.</li><li>Awareness of the open-source AI tooling ecosystem (Continue.dev, Aider, Cline, Ollama). Exposure to building or customizing AI agents/skills using LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) for engineering automation such as code review, documentation, or migration assistants.</li><li>Live and breathe testing.</li></ul>

Responsibilities: Software Development: <ul><li>Design, develop, test, and maintain scalable software applications using Java Spring Boot and JavaScript for backend and frontend development, respectively. Build clean, reusable, maintainable, and well-tested code following software engineering best practices.</li></ul> Full Stack Application Development: <ul><li>Develop end-to-end web and mobile applications using Java Spring Boot, React or React Native, backend APIs, database integrations, and modern UI frameworks to deliver intuitive user experiences.</li><li>Design and develop secure RESTful APIs, backend services, authentication mechanisms, and data access layers while ensuring application scalability and performance.</li></ul> AI Enable Engineering: <ul><li>Leverage AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, Amazon Q, or similar tools to improve engineering productivity.</li><li>Experience integrating LLM APIs or AI-powered capabilities into applications is desirable.</li></ul> Collabration: <ul><li>Collaborate with Product Managers, Business Analysts, UX Designers, QA Engineers, Architects, and cross-functional engineering teams to understand business requirements and deliver scalable software solutions.</li><li>Participate in sprint planning, technical discussions, estimation, backlog refinement, and Agile ceremonies.</li></ul> Testing &amp; Quality: <ul><li>Develop unit tests, integration tests, and participate in peer code reviews to ensure software quality, maintainability, reliability, and performance.</li><li>Follow secure coding standards and engineering best practices.</li></ul> Cloud &amp; Devops: <ul><li>Contribute to CI/CD pipelines and cloud-native application deployments using technologies such as Docker, Kubernetes, Azure, AWS, GitHub Actions, or Azure DevOps.</li></ul> Continous Improvement: <ul><li>Identify opportunities to improve software architecture, engineering standards, automation, developer productivity, and application performance.</li><li>Adopt AI-assisted engineering workflows and modern software development practices.</li></ul> Technical Support: <ul><li>Troubleshoot production issues, perform root cause analysis, and resolve application issues while ensuring minimal business disruption.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).</li><li>3–5 years of professional software development experience.</li><li>Minimum 3+ years of hands-on full-stack development experience.</li><li>Experience developing production-grade web or mobile applications (not academic or personal projects).</li><li>Strong proficiency in Java Spring Boot and JavaScript.</li><li>Experience developing applications using React or React Native.</li><li>Experience developing backend services using Node.js or equivalent backend technologies.</li><li>Strong understanding of REST API development.</li><li>Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or equivalent.</li><li>Strong knowledge of Git and modern software engineering practices.</li><li>Experience working in Agile/Scrum teams.</li><li>Strong understanding of object-oriented programming, software design principles, and data structures.</li></ul>

Responsibilities: People, Talent and Cross-Functional Collaboration:&nbsp; <ul><li>Ensure optimal staffing levels across front-end, back-end, full-stack, and platform specializations.&nbsp;</li><li>Hire, coach, and develop top-tier engineering talent.</li><li>Manage direct reports and technical leads, address performance issues promptly, and build strong relationships with Product, Design, Platform, Data, and agile train leadership to deliver cohesive, customer-focused solutions.</li><li>Community of Practice, Developer Experience and AI-Driven Engineering: As AI tooling becomes inseparable from modern engineering practice, own the convergence of Community of Practice standards and AI adoption as a single discipline.&nbsp;</li><li>Foster best practice adoption across the engineering community with AI tooling treated as a first-class part of the practice.</li><li>Define standards for responsible AI adoption — including when to use AI coding assistants, agents, skills, and MCP integrations versus traditional approaches.</li><li>Establish clear guidance on the distinction between AI Skills (deterministic capabilities) and Agents (autonomous, multi-step workflows). </li><li>Evaluate, pilot, and roll out AI tools (GitHub Copilot, Claude Code, Cursor, Windsurf, Continue.dev, Aider, Cline, Ollama). </li><li>Define governance for AI use in regulated financial services contexts including data handling, PII protection, IP compliance, and code provenance. </li><li>Track and measure the combined impact of CoP practices and AI adoption on cycle time, PR throughput, defect rates, and developer satisfaction.</li><li>System Architecture and Technical Direction: Own a modern view of system architecture spanning client, server, data, integration, and AI layers.&nbsp;</li><li>Champion patterns such as micro-frontends, BFF, event-driven, API-first, serverless, and composable architectures.&nbsp;</li><li>Partner with Enterprise Architects on platform alignment.&nbsp;</li><li>Guide trade-off decisions (monolith vs. microservices, sync vs. async, build vs. buy). Use AI-powered architecture tools to accelerate design exploration and generate ADRs.</li><li>Ensure teams document decisions so both humans and AI agents can reason about the system. </li><li>Understand how AI tools interact with system architecture — including RAG, vector databases, MCP integrations, and agentic workflows.</li></ul> Strategic Planning, Delivery and Operational Excellence:&nbsp; <ul><li>Ensure plans align with CoP goals, review quarterly commitments to flag risks early, and step in to resolve conflicts between product, design, and engineering.&nbsp;</li><li>Drive CI/CD best practices, ensure high-quality scalable solutions across the stack, and provide on-call support during escalations.&nbsp;</li><li>Support tech leads hands-on when needed, regardless of which layer of the stack the problem lives in.</li></ul> Requirements: <ul><li>Strong hands-on background in modern front-end technologies (ReactJS, TypeScript, NextJS, Cypress) as an anchor foundation, with working knowledge of back-end technologies, APIs, microservices, and data layer concepts.&nbsp;</li><li>Experience with AWS cloud services, CI/CD pipelines, and modern DevOps practices.&nbsp;</li><li>Proven ability to lead engineers working across the full stack.</li><li>Solid grounding in system architecture fundamentals — distributed systems, scalability, CAP trade-offs, caching, messaging, API design — and familiarity with modern patterns (micro-frontends, BFF, event-driven, CQRS, serverless, composable architectures).&nbsp;</li><li>Experience making and documenting architecture decisions (ADRs), with understanding of how AI-native architecture (RAG pipelines, vector databases, agent orchestration) differs from traditional architecture.</li><li>Hands-on experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) with clear understanding of the difference between AI Skills and Agents, familiarity with MCP (Model Context Protocol), RAG patterns, and experience defining AI usage guidelines and governance frameworks for regulated environments.&nbsp;</li><li>Awareness of the open-source AI tooling ecosystem (Continue.dev, Aider, Cline, Ollama).</li><li>Proven experience leading and growing high-performing engineering teams, running or contributing to a Community of Practice, and strong communication skills with the ability to influence across organizational levels.</li></ul>

Responsibilities:&nbsp; <ul><li>Support the implementation and enhancement of Enterprise Datahub using Databricks, ensuring seamless integration with existing BI and ERP systems.</li><li>Support complex BI and data platform initiatives while maintaining quality, delivery timelines, and alignment with organizational goals.</li><li>Collaborate with business stakeholders, architects, developers, and analysts to translate requirements into solutions.</li><li>Design, implement, test, and optimize moderately complex data pipelines, ETL/ELT flows, semantic layers, and report solutions with the development team.</li><li>Apply technical knowledge and AI-driven optimization opportunities to improve data quality, validation, reliability, and operational efficiency across supported solutions.</li><li>Develop new and impactful ideas, approaches, and automation opportunities that improve the platform, processes, and user experience.</li><li>Communicates moderately complex information clearly, accurately, and in a timely manner, adapting the message to the audience.</li></ul> Requirements: <ul><li>Degree in Business Informatics, Information Technology, Data Engineering/Analytics, Engineering, or a related field.</li><li>Proven experience in data engineering, application support, BI analytics, or related technical roles.</li><li>Strong expertise in Databricks, GitHub, dbt, ETL, Tableau, Power BI, and SQL.</li><li>Familiarity with Generative AI tools (e.g., Copilot, LLM-based assistants) to enhance productivity, development, and documentation.</li><li>Ability to analyze moderately complex problems independently and drive resolution with minimal supervision.</li><li>Strong stakeholder management, teamwork, and clear written and verbal communication skills.</li><li>Experience contributing to technical improvements, process optimization, and operational quality.Proficiency in English, both written and spoken.</li></ul>

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>

Responsibilities: <ul><li>Technical Leadership &amp; Strategy: Create long-term Integration Strategy and Roadmap, Define and implement Integration patterns &amp; standards</li><li>Technology Evaluation: Research, evaluate, and adopt emerging technologies, tools, and industry trends to enhance integration capabilities</li><li>Solution Architecture: Design scalable and reusable middleware components, including API gateways, message brokers, iPaas and application servers</li><li>Infrastructure Management: Deploy, manage and monitor integration solutions to ensure high availability, optimal performance and minimal downtime</li><li>Governance &amp; Standards: Establish and enforce best practices, security measures, and documentation standards for middleware platforms</li><li>Collaboration &amp; Leadership: Ability to work across teams, mentor engineers, and communicate technical strategies to stakeholders.</li><li>Experience: Substantial experience in multiple middleware technologies for architecture design, software development and system administration in both cloud-native and hybrid environments</li><li>Systems Thinking: Ability to evaluate, design and maintain future ready, secure, scalable digital integration solutions.</li></ul> Requirements: <ul><li>Minimum requirement of 8 years of relevant work experience. Typically reflects 12 years or more of relevant experience.</li><li>Technical Expertise: Strong proficiency with middleware technologies such as</li><li>Integration Platforms: Boomi, SAP BTP, MuleSoft</li><li>API Gateways: Kong, Layer7, Apigee</li><li>B2B/EDI: Open Text, Boomi, IBM Sterling</li><li>Messaging Queue: Kafka, Solace, Pulsar</li><li>Web/App Servers: WebLogic, WebSphere, Tomcat</li><li>Technical Services: Jira, GitHub, Azure DevOps, Datadog, AppDynamics</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: <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>

Role Description: <ul><li>Company’s Global R&amp;D team is looking for embedded software engineers and technical leaders to help build the future of industrial Automation &amp; Solutions.</li><li>You will have cross functional interactions and working closely with hardware, software, and product management teams.</li></ul> Responsibilities: As a Lead Software Engineer, the individual will work be in Embedded Software Development team. <ul><li>You provide the embedded platform infrastructure to enable our Industrial Networking Products.</li><li>You dedicate your creativity to a cross-functional, self-organized, agile team of developers.</li><li>You communicate with product owners, software architects and application developers in an intercultural and global work environment.</li><li>You contribute to the implementation of a Linux based Operating system for in-field embedded device families.</li><li>You assure the secure development life cycle of the platform and harden the attack surface of devices.</li><li>You will be part of the Software Platforms Teams, working on the development of in-house cybersecurity device software development for Industrial networks.</li><li>You will be building Firewall software for industrial routers which are complex multicore, multi-threaded software systems supporting high-availability, hundreds of network protocols and delivering high throughput packet forwarding.</li><li>Building brand new products, supporting new features, feature enhancements and sustenance of products across the R&amp;D product portfolio, using company’s device software running on company hardware.</li></ul> Requirements: <ul><li>You are a person with passion for coding and creating world class software systems for large organizations.</li><li>A Full time Bachelor/Master of Engineering Degree in Computer Science or equivalent.</li><li>You are able to abstract and use your creativity for disruptive solutions.</li><li>You are fluent in spoken and written English and have the ability or willingness to work in a Global environment</li><li>8 – 12 years’ experience in a product-based organization developing embedded software for Enterprise, Industrial Automation or Service Providers industry.</li><li>Solid understanding of embedded systems architecture, including microcontrollers, microprocessors, and real-time operating systems.</li><li>Ability to work on complex modular software systems, algorithms and be able to design, code, debug and automate software.</li><li>Expertise in C/C++ programming, data structures, Algorithms &amp; debugging tools.</li><li>Expertise in Linux based environment, with extensive knowledge of Linux Internals.</li><li>Hands-on operating systems, IPCs &amp; multi-thread programming experience.</li><li>Advanced working level knowledge of Computer networks and Network protocols in TCP/IP, switching (L2), routing (L3) &amp; security protocols.</li><li>One or more areas like QOS, Segment Routing, Multicast &amp; MPLS.</li><li>Ability to work with existing code base.</li><li>Hands-on experience in Versioning and Git/GitHub/Bitbucket repository.</li><li>Experience with Unit test strategy and execution.</li><li>Experience with Python or equivalent scripting languages</li><li>Experience with packet generating and network test tools.</li><li>Prior experience with any network OS provided by Networking companies like CISCO -IOS/IOS-XE/IOS-XR.</li><li>Designing &amp; understanding of network topologies &amp; deployment.</li><li>Linux containers and dockers.</li></ul>

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11 github Jobs found

AVP, Principal Software Engineer (Front-End)

Software Engineer – Ag & Trade

VP, Engineering Manager

Senior IT Engineer

Lead Quality Automation Engineer

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

Lead Software Engineer, QA

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11 github Jobs found

AVP, Principal Software Engineer (Front-End)

Software Engineer – Ag & Trade

VP, Engineering Manager

Senior IT Engineer

Lead Quality Automation Engineer

Principal Platform Engineering – Digital Integration

Senior Machine Learning Engineer (Production & MLOps Focus)

QA Tester

Consulting Principal AWS Cloud Engineer

Lead Software Engineer, QA

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

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