Databricks AI/ML Developers (AgentBricks/Python Coding)
Posted Today by Nasscomm, Inc.
Negotiable
Undetermined
Remote
Remote
Summary: The role of Databricks AI/ML Developer focuses on building rapid AI prototypes using Databricks, specifically targeting FEMA's data. The position emphasizes lightweight and fast-moving agent and GenAI prototypes, primarily utilizing Agent Bricks. The developer will work closely with FEMA program teams to scope AI use cases and collaborate with data engineers to ground agents in governed data products. This is a contract position lasting 2-3 months and is fully remote.
Key Responsibilities:
- Build agent prototypes on Databricks using Agent Bricks that solve concrete FEMA workflow problems and can be demonstrated quickly.
- Scope lightweight, decentralized AI use cases with FEMA program teams, favoring quick wins over long modeling cycles.
- Ground agents in governed data products from Unity Catalog, in close collaboration with data engineers.
- Surface agent capabilities via Databricks Apps front-ends by exposing Databricks APIs to the front end team.
Key Skills:
- Experience with Databricks and Agent Bricks.
- Proficiency in Python coding.
- Ability to build AI prototypes quickly.
- Strong collaboration skills with program teams and data engineers.
- Understanding of AI use cases in a decentralized context.
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Role Title: Role Title: Databricks AI/ML Developer (AgentBricks/Python Coding)
Contract: 2-3 Months
Location: Remote
Build rapid, working AI prototypes that demonstrate value on FEMA''s data in Databricks.
The priority is lightweight, fast-moving agent and GenAI prototypes, primarily with Agent Bricks, but also includes other GenAI features such as MCPs and the Databricks Agentic Framework.
Key Responsibilities:
- Build agent prototypes on Databricks using Agent Bricks that solve concrete FEMA workflow problems and can be demonstrated quickly.
- Scope lightweight, decentralized AI use cases with FEMA program teams, favoring quick wins over long modeling cycles.
- Ground agents in governed data products from Unity Catalog, in close collaboration with data engineers.
- Surface agent capabilities via Databricks Apps front-ends be exposing databricks APIs to the front end team.