AI and Data Engineer
Kasmo· enterprise· Information Technology And Services· Sep 29, 2026 · 29d ago
Jersey City, NJ
Hybrid
Full-time
Mid
$100K–$160K est.
Job description
Description:
Locations: NY/NJ, Tempe (Arizona), Tempa (Florida)
Hybrid: Work from office 3 days a week
Job Profile - AI and Data Engineer
Position details:
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
· Ensure high quality and optimum performance of data systems to meet business expectations.
Job Requirements:
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.
Skillset Rubric -
Business Acumen – 15%: Knowledge of Banking & Financial Services Products (such as Loans, Deposits, Forex, etc.). Knowledge of Operational/MIS Reports, Risk and Regulatory Reporting for a Client is a plus.
Data Skills – 25%: Must have proficiency in Data Warehousing concepts, Data Lake & Data Mesh concepts, Data Modeling, Databases, Data Governance, Data Security/Protection, and Data Access.
Tech Skills – 50%: Hands-on data and software engineering using Python, Java, TypeScripts, SQL, AWS, Snowflake, Starburst, BI platforms, GitHub Copilot, LLM/RAG and agent frameworks, MCP/API integrations, Playwright/browser automation, automated testing, observability, and secure enterprise deployment practices.
Human Skills – 10%: Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
Application prep
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Keywords to mirror
aiawsllmsqlci/cdpythonjavaapi
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