Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

Senior Software Engineer 1 (.Net)

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

IAD / SAD Developer Ansible OpenShift

Senior Machine Learning Engineer (Production & MLOps Focus)

System engineer

Senior DevOps Engineer

Consulting Principal AWS Cloud Engineer

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: <ul><li>Demonstrate accountability by ensuring timely and high-quality project delivery.</li><li>Be result driven, consistently achieving measurable outcomes and meeting goals.</li><li>Act as a team player, collaborating effectively with cross-functional teams.</li><li>Exhibit a can-do mentality, tackling challenges with a proactive and positive approach.</li><li>Apply software engineering patterns and principles to design, develop, test, integrate, maintain, troubleshoot and document complex and varied software solutions and incorporate security practices in newly developed and maintained applications.</li><li>Participate in peer code review sessions to review code, coach peers and ensure code quality.</li><li>Take the lead in the assigned agile team to adopt agile philosophies, facilitate agile ceremonies and identify continuous improvement opportunities.</li><li>Incorporate the companys engineering and development best practices within the full software development lifecycle including coding standards, code reviews, source control management, building processes, testing and security principles, to deliver high quality code rapidly.</li><li>Collaborate to lead demonstration and continuous feedback sessions to improve development and help drive the long term vision.</li><li>Participate in the engineering community by maintaining and sharing relevant technical approaches and modern skills.</li><li>Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff.</li><li>Other duties as assigned</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field or equivalent experience</li><li>Confirmed experience automating pipelines for continuous integration, testing, delivery and security.</li><li>Confirmed experience architecting applications, databases, services or integrations.</li><li>Extensive experience with .NET Framework and .NET Core.</li><li>Familiarity with front-end technologies like HTML, CSS, JavaScript, and frameworks such as Angular, React, or Vue.js.</li><li>Experience with DevOps practices and tools such as Docker and CI/CD pipelines.</li><li>Knowledge of SQL Server and / or PostgreSQL for database design and management.</li><li>Hands-on experience with Kubernetes for container orchestration and management.</li><li>Experience with cloud platforms such as Azure, AWS, or GCP.</li><li>Minimum of 5 years of related work experience in software development using .NET technologies.</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust, scalable, and secure web applications.</li><li>Utilize Object-Oriented design principles and best practices to ensure high-quality software.</li><li>Write clean, efficient, and well-documented code in C# with both .NET Core and .NET Framework.</li><li>Ensure adherence to Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Create and manage CI/CD pipelines using tools like Jenkins, GitLab CI, or Azure DevOps.</li><li>Automate repetitive tasks in the software development lifecycle, including builds, testing, and deployments.</li><li>Configure and maintain infrastructure for CI/CD pipelines, including servers and containerized environments.</li><li>Leverage cloud platforms like AWS, Azure, or GCP for scalable infrastructure and application management.</li><li>Incorporate DevOps principles to foster collaboration between development and operations teams.</li><li>Integrate unit testing frameworks (e.g., NUnit) into pipelines to ensure robust software quality.</li><li>Utilize test-driven development practices to enhance software reliability.</li><li>Work closely with developers, QA engineers, and operations teams to streamline workflows and address feedback.</li><li>Demonstrate strong communication skills to present ideas, solutions, and progress effectively.</li><li>Monitor CI/CD pipeline execution and troubleshoot issues promptly to minimize downtime.</li></ul> Requirements: <ul><li>Demonstrated knowledge of software application development (certifications and experience considered in lieu of a degree).</li><li>6+ years of experience in software development using C# and .NET.</li><li>5+ years of experience in developing .NET applications, including .NET Core and .NET Framework.</li><li>Proven experience in building enterprise-level web applications.</li><li>Strong background in Object-Oriented design and development.</li><li>Advanced JavaScript experience, including closures and prototype inheritance.</li><li>Proficiency in SQL (DDL and DML) and experience managing database structures.</li><li>Solid understanding of Web Standards (XML, JSON, HTML, CSS, APIs, Web Services).</li><li>Demonstrated use and knowledge of design patterns and cloud-native technologies.</li><li>Experience with Agile methodologies and iterative development processes.</li><li>Proficiency in CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline is required.</li></ul> Preferred work experience and skills: <ul><li>Strong proficiency in C#, JavaScript, and scripting languages like Bash, Python, or PowerShell for task automation.</li><li>Expertise in popular CI/CD platforms like Jenkins, GitLab CI, Azure DevOps, or AWS Code Pipeline.</li><li>Deep understanding of Git and branching strategies for effective code management.</li><li>Familiarity with unit testing frameworks like Unit, JUnit to integrate automated testing into pipelines.</li><li>Knowledge of cloud platforms like AWS, Azure, or GCP for scalable infrastructure management.</li><li>Familiarity with containerized environments (e.g., Docker, Kubernetes) and microservices architecture.</li><li>Exceptional problem-solving and analytical skills.</li><li>Strong communication and collaboration abilities.</li><li>Self-motivated and able to work independently with minimal supervision.</li><li>Detail-oriented with excellent organizational skills.</li></ul>

Responsibilities: <ul><li>Lead the design and development of LLM-powered solutions for clinical summarization, intelligent chat, and document understanding to improve patient care outcomes.</li><li>Architect and implement end-to-end machine learning pipelines, including Retrieval-Augmented Generation (RAG) systems using vector databases such as Pinecone and Weaviate.</li><li>Fine-tune and optimize state-of-the-art language models (e.g., GPT, LLaMA, Mistral) and apply advanced prompt engineering to address specialty-specific healthcare use cases.</li><li>Own project delivery end to end, collaborating with stakeholders to ensure AI solutions are ethical, scalable, reliable, and well-governed.</li><li>Mentor and support junior data scientists, fostering a culture of experimentation, learning, and innovation.</li></ul> Requirements: <ul><li>Experience: 8–12 years in Data Science/ML, with at least 3+ years specifically focused on LLMs and Generative AI.&nbsp;</li><li>Technical Mastery: Deep hands-on expertise in Python and frameworks like PyTorch, Hugging Face, LangChain, or LlamaIndex.&nbsp;</li><li>Cloud Fluency: Proven ability to deploy models at scale using AWS SageMaker, Azure ML, or GCP Vertex AI.&nbsp;</li><li>MLOps Mindset: Experience with MLflow, Airflow, Docker, and Kubernetes to ensure our "bold innovations" are also stable and reliable.&nbsp;</li><li>Academic Foundation: A strong grasp of statistical analysis and evaluation techniques to mitigate hallucinations and ensure clinical accuracy.&nbsp;</li></ul>

Responsibilities: Architecture &amp; Design:&nbsp; <ul><li>Design end-to-end data architectures that integrate real-time streaming (Kafka, GCP Pub/sub) and batch processing (Big Query OR Databricks).</li></ul> Pipeline Development:&nbsp; <ul><li>Build and maintain robust ETL/ELT pipelines flowing into BigQuery/Databricks, ensuring data is clean, modeled, and ready for consumption.</li></ul> Custom Integration:&nbsp; <ul><li>Develop custom APIs and microservices using Java/Python/C# to facilitate data movement between niche systems and the data lakehouse.</li></ul> Infrastructure Management:&nbsp; <ul><li>Deploy and manage data workloads on Google Kubernetes Engine (GKE), ensuring high availability and cost-efficiency.</li></ul> Technical Leadership:&nbsp; <ul><li>Mentor junior engineers, conduct code reviews, and establish DataOps best practices (CI/CD, automated testing, and monitoring).</li></ul> Data Reliability:&nbsp; <ul><li>Implement data quality frameworks to ensure accuracy and lineage across the hybrid environment.</li></ul> Requirements: <ul><li>Experience with Terraform &amp; Azure Dev Ops (ADO).</li><li>Knowledge of workflow orchestrators like Apache Airflow (Cloud Composer).</li><li>Experience implementing Data Governance (metadata management, data cataloging).</li><li>Data Processing &amp; Storage</li><li>BigQuery: Expert-level SQL and experience with partition/cluster optimization.</li><li>Databricks: Deep knowledge of the Lakehouse architecture, Delta Lake, and Spark (PySpark/Scala) Software Engineering &amp; APIs</li><li>Languages: Proficiency in Java/Python/C# for backend development and custom data connectors.</li><li>API Design: Proven ability to build and consume RESTful APIs for data ingestion Streaming &amp; Infrastructure</li><li>Kafka/GCP Pub-Sub: Experience building event-driven architectures and managing producers/consumers.</li><li>GKE: Proficiency in containerization (Docker) and orchestrating data workloads on Kubernetes.</li></ul>

Responsibilities: <ul><li>Perform systems analysis and design for applications deployed using Ansible and OpenShift.</li><li>Design and develop moderate to complex applications in alignment with business and technical requirements.</li><li>Create, maintain, and ensure accuracy of comprehensive application documentation.</li><li>Define, build, and deliver application and system integration builds.</li><li>Monitor, evaluate, and apply emerging technology trends to improve system architecture and development practices.</li></ul> Requirements: <ul><li>5+ years of experience</li><li>Bachelor’s Degree or International equivalent&nbsp;</li><li>Extensive experience with core Java concepts and Java EE.</li><li>Extensive experience with Spring and Spring Boot.</li><li>Experience with CI/CD code automation, Ansible &amp; DevOps</li><li>Experience with OpenShift</li><li>Good understanding of software architecture and design principles.</li><li>Understanding of data structures, programming logic, and design</li><li>Understanding of application design patterns</li><li>Excellent written &amp; verbal communication skills</li><li>Excellent attention to detail</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>Provide application L1/L2 support and system checks (CPU, disk usage, logs, services)</li><li>Troubleshoot and resolve system and application issues, and provide on-site technical support to ensure timely resolution and minimal disruption to business operations</li><li>Monitor application health and system alerts, escalating issues as needed</li><li>Log incidents and service requests in the ticketing system, ensuring timely resolution</li><li>Coordinate with L3 teams and vendors for issue escalation and follow-up</li><li>Perform routine maintenance tasks, such as application updates, patching, and backups</li><li>Maintain clear documentation of issues, fixes, and procedures</li><li>Participate in system testing, deployment, and post-deployment support activities</li><li>Assist in user access management and configuration </li><li>Requirements:</li><li>Diploma/Degree in Electrical Engineering, Computer Science, Communications Engineering or equivalent</li><li>Minimum 2 years in application maintenance, support or server infrastructure setup</li><li>Experience participating in Kubernetes cluster projects, with proficiency in using relevant commands to check application logs</li><li>Experience with at least two of the following Virtualization Technology/Platforms: VMware, Xen, KVM, OpenStack, Cloud Stack, Azure Stack</li><li>Experience with cloud orchestration, configuration management and auto-scaling techniques</li><li>Thorough knowledge of networking, routers, switches, and WiFi setup</li><li>Hands on experience in deploying ceph using different file system such as object storage, rbd, cephfs storage</li><li>Good knowledge of storage technologies, such as NAS, SAN, SDS</li><li>Experience with automation tools such as Salt/Chef/Puppet/Ansible</li><li>Experience with load balancing setup for TCP/IP, HTTP, DNS, routings.</li><li>Experience in using software version control</li><li>Knowledge of IT security standards, for instance from CIS or IM8.</li><li>Experience in IT security policy management and enforcing IT security</li><li>Knowledge of computer hardware components and ability to restore faulty servers to working condition.</li><li>Experience in coding or scripting languages such as bash, windows batch script, powershell, perl, python, etc.&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>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.&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.&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.&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.&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.&nbsp;</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.&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.</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.&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.&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.&nbsp;</li><li>Demonstrated ability to drive cultural change and advocate for cloud transformation Responsibilities&nbsp;</li><li>Develop and implement a comprehensive AWS cloud strategy, ensuring alignment with business and technology goals.&nbsp;</li></ul>

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12 kubernetes Jobs found

Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

Senior Software Engineer 1 (.Net)

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

IAD / SAD Developer Ansible OpenShift

Senior Machine Learning Engineer (Production & MLOps Focus)

System engineer

Senior DevOps Engineer

Consulting Principal AWS Cloud Engineer

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12 kubernetes Jobs found

Data & ML Architect

Sr. Software Engineer - Ag & Trading .Net

Senior Software Engineer 1 (.Net)

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

IAD / SAD Developer Ansible OpenShift

Senior Machine Learning Engineer (Production & MLOps Focus)

System engineer

Senior DevOps Engineer

Consulting Principal AWS Cloud Engineer

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.