AI Data Engineer

Key Responsibilities

• Agent Design and Development: Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules.
• Data Engineering & Integration: Design and develop data pipelines supporting AI and machine learning workloads. Ensure data quality, lineage, governance, and security requirements are met.
• Machine Learning Integration: Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making.
• Software Engineering: Develop production-grade applications and APIs using Python and/or Java. Build reusable services, microservices, and AI components.
• Framework and Tooling: Utilize and contribute to agentic AI frameworks and development tools.
• Research and Innovation: Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions.
• Collaboration: Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services.
• Documentation: Create comprehensive technical documentation for agent designs, implementations, and operational procedures.

Required Qualifications

• Experience: 5+ years of professional experience in software development. 2+ years working with AI/ML, Generative AI, or intelligent automation solutions. Financial services experience preferred.
• Programming: Strong proficiency in Python, SQL; Java is a plus.
• AI/ML Expertise:
• Experience working with Generative AI and LLM-based applications.
• Knowledge of Prompt Engineering, RAG, embeddings, vector DBs, and agentic frameworks.
• Familiarity with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
• Experience utilizing OpenAI, Azure, Anthropic, Gemini, Bedrock, or equivalent platforms.
• Understanding of machine learning fundamentals and model evaluation technique.
• Data Engineering: Experience designing and supporting data pipelines and data integration workflows.
• Problem-Solving: Excellent analytical and problem-solving skills with a creative approach to complex challenges.
• Communication: Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.
• Platforms : Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Domain – Finance preferable
• Collaboration – Able to collaborate within and across teams and organizations
• Education:
• Bachelor’s degree/University degree or equivalent experience
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Job Family Group:

Primary Location Full Time Salary Range:

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Most Relevant Skills

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Automated Processing and AI