AI and Data Engineer

• Candidates should have hands-on experience using GitHub Copilot and engineering AI agents that combine Large Language Models (LLMs), prompt and context engineering, Retrieval-Augmented Generation (RAG), APIs, enterprise data sources, and governed tool execution to automate data, reporting, testing, and operational workflows.
• Successful candidates will possess in-depth knowledge of current and emerging technologies, demonstrate a passion for designing and building elegant solutions, and continuously improve engineering efficiency through responsible, secure, observable, and testable adoption of AI technologies.
• In this role, you will work with technology and business leads to build or enhance critical enterprise data applications both on-prem and in the cloud (AWS), leveraging modern data platforms such as Snowflake and Starburst.

Roles and Responsibilities:

• Use GitHub Copilot as a hands-on engineering environment to analyze existing code, design and implement production-quality changes, generate and maintain tests and documentation, debug failures, review proposed changes, and verify outcomes with executable evidence.
• Design, build, test, and operate AI agents that plan and execute multi-step workflows using LLM reasoning, structured prompts, context and memory, retrieval, APIs, data tools, and human approval gates to enhance data engineering, reporting, testing, and operational processes.
• Develop tool-enabled agents and Model Context Protocol (MCP) integrations that securely connect AI assistants to enterprise APIs and platforms, including BI/reporting services, data products, work-management systems, and operational knowledge sources.
• Implement browser and UI automation agents for authenticated enterprise workflows, evidence capture, regression testing, test generation and healing, and operational workflows, using tools such as Playwright and browser developer protocols.
• Define agent evaluation, observability, and safety controls, including grounded-response checks, deterministic tool contracts, structured outputs, least-privilege credential handling, approval checkpoints, test datasets, execution traces, failure recovery, and measurable quality and productivity outcomes.
• Develop and implement data mesh and data fabric architectures to enable decentralized data management and access.
• Design, build, and deploy cloud-native AI, data, and analytics solutions on AWS using serverless, containerized, and event-driven architectures.
• Develop automated deployment pipelines and cloud integrations to enable secure, scalable, and reliable delivery of AI agents, data products, and reporting solutions.
• Build data and BI development agents that generate and validate SQL, DAX, semantic models, reports, data-product specifications, quality tests, and deployment artifacts while preserving governance, auditability, and human review.
• Develop user personas and business personas in alignment with data requirements and deliver solutions that meet business needs.
• Work with business users to translate functional specifications into technical designs for implementation and deployment
• Work with cross functional team members to develop prototype, produce design artifacts, develop components, perform and support SIT and UAT testing, triaging and bug fixing.
• Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs
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• Bachelors’ Degree (or foreign equivalent degree) in Information Technology, Information Systems, Computer Science, Software Engineering, or a related field. Experience in the financial services or banking industry is preferred.
• 2+ years of hands-on experience using GitHub Copilot or similar AI-assisted engineering tools across the software development lifecycle, including requirements analysis, coding, refactoring, testing, debugging, documentation, code review, and verification.
• 2+ years of hands-on experience designing and building Agentic AI solutions using prompt and context engineering, LLMs, RAG, structured tool/function calling, APIs, memory or state management, human-in-the-loop controls, and AI governance principles.
• 3+ years of experience developing and deploying cloud-native applications on AWS, including serverless, container, event-driven, security, and CI/CD patterns.
• Hands-on programming experience in Python, Java, TypeScripts and SQL, with the ability to design agent tools, API clients, MCP servers, command-line workflows, typed data contracts, and automated tests for enterprise use cases.
• Experience integrating agents with enterprise authentication, APIs, databases, knowledge repositories, BI platforms, and browser automation while protecting credentials, sensitive data, and audit trails.
• Demonstrated ability to evaluate agent quality through unit, integration, behavioral, and end-to-end tests; diagnose hallucinations and tool failures; instrument execution; and improve prompts, retrieval, context, and workflows using evidence.
• Broader candidate background preferences -
• 5+ years of experience with data virtualization, data mesh, data fabric, and federated querying platform such as Denodo, Starburst or OSS platforms is highly desirable.
• 5+ Years of experience working as a Report Visualization Engineer with Power BI, Tableau, or any similar Reporting Platforms with End-to-End delivery.
• 3+ Year of experience with implementation of Data Modelling, Data Governance and RLS.
• 3+ Years of experience with Enterprise Deployment Strategies and migration of legacy platform reports to modern reporting platforms.
• Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms like Snowflake.
• Solid understanding of data modeling, database design, and ETL principles.
• Familiarity with data governance, data security, and compliance practices in cloud environments.
• Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance.
• Tableau/Power BI / Snowflake / Starburst certifications on Data related specailities are a plus.
• Power Platform experience (Power Apps, Power Automate) will be a plus.