About the Role
We’re looking for an Entry Level Developer passionate about data engineering, automation, and AI. You’ll work alongside senior architects to help design and build components of our data context and AI orchestration framework (MCP) — connecting master data, metadata, and intelligent agents across enterprise systems.This is not a routine reporting role. It’s hands-on coding, API integration, and experimenting with how AI interacts with structured and unstructured data to make enterprises more intelligent.
Key Responsibilities
- Develop and test Python-based scripts, APIs, and data pipelines to automate ingestion and enrichment.
- Assist in building metadata connectors and context services that integrate with AI agents.
- Prototype small LLM or GenAI utilities that help analyze, tag, or summarize enterprise data.
- Support in deploying and monitoring AI-driven workflows (data quality scoring, entity matching, recommendations).
- Collaborate with data architects to model and validate master and reference data entities.
- Document APIs, logic, and test results for governance and reusability.
- Required Skills 1-3 year of hands-on development experience (internships count).
- Strong programming fundamentals — Python, JSON, REST APIs.
- Working knowledge of SQL and basic data engineering workflows (ETL/ELT, data cleaning).
- Curiosity about LLMs, AI automation, and metadata-driven architectures.
- Understanding of data quality and governance concepts is a plus.
- Exposure to Git, notebooks, or lightweight cloud tools (any platform) preferred.
- Nice to Have / Learn On the Job Familiarity with MCP (Model Context Protocol) or context-based API frameworks.
- Experience with prompt engineering or lightweight GenAI integrations.
- Understanding of data models, lineage, or entity resolution logic.
- Scripting for data validation or metadata tagging.
- Soft Skills Problem solver with a builder mindset — eager to automate, not just analyze.
- Strong communicator and team player.
- Self-learner who’s curious about how AI agents reason with data.
- Growth Path Within 12–18 months, you’ll gain exposure to: Enterprise MDM and metadata frameworks (Reltio, Informatica).
- Context-driven AI architecture (MCP).
- Advanced GenAI automation and semantic data modeling.
- Building intelligent agents that operate on governed enterprise data.
Why Join Us
You’ll be part of a fast-growing Data + AI architecture team designing systems that make enterprise data think for itself. Learn how to build pipelines that talk to AI agents, design metadata that fuels intelligence, and work with cutting-edge frameworks combining data engineering, automation, and contextual AI.
