About the role

You build the AI agents at the heart of M-agentic — Agentic Process Studio. Working within the agent squad, you implement and test the agents that automate a real Health Insurance Claim Adjudication process on AWS AgentCore + Amazon Bedrock (Claude) — writing the prompts, tools, guardrails and integrations that make each agent reliable, safe and auditable.

Key responsibilities

- Implement worker and application agents on AWS AgentCore / Bedrock: prompts, tool definitions, control flow and hand-offs between steps.
- Engineer and iterate prompts for the Studio's AI features (intake parsing, gap analysis, agent-blueprint generation) and contribute test cases to the eval harness.
- Integrate enterprise systems as governed tools (API connectors / MCP tools) for the six claims systems (Availity, HealthEdge, Optum, Shift, Zelis, InterQual) using sandbox adapters.
- Wire safety and compliance into every agent: Bedrock Guardrails, PHI masking, and the immutable audit trail.
- Write clean, tested Python; participate in code review and pair with the Lead and peers.
- Help implement the human-in-the-loop gates (clinical review, SIU) and the Forge deploy path.
- Debug agent behaviour using traces,



logs and evals; tune model choice and cost per step.

Required qualifications

- 2+ years in software or ML engineering with strong Python.
- Practical experience with LLM applications — prompt engineering, tool/function calling, and at least one agent or RAG project (skilled, open-source or substantial personal).
- Working knowledge of AWS (Lambda, IAM, S3, and event-driven basics).
- Solid fundamentals: version control, testing, APIs, JSON/data handling.
- Curious, detail-oriented, and comfortable with fast iteration and measurement.

Preferred

- Exposure to Amazon Bedrock, AWS AgentCore, Bedrock Agents, LangGraph/LangChain, or MCP.
- Experience integrating third-party APIs or building connectors.
- Interest in AI safety, guardrails, evals, or regulated-data handling.

What success looks like (first 8 weeks)

- Owns one or more worker agents end-to-end — built, tested and running in the pipeline.
- Contributes reliable prompts and eval cases that raise output quality measurably.
- Ships steadily within the squad's cadence with clean, reviewed code

📌 Gen AI Developer / Lead / Architect (Hyderabad)
🏢 Perfect Job Accord
📍 Hyderabad