Gen AI Developer / Lead / Architect
Perfect Job Accord · Hyderabad · onsite · Posted 58d ago
About a minute. You'll make an account on the way through.
About this role
## 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 (professional, 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
Sourced from naukri