Senior AI/ML Engineer

Pmr Softtech

Chennai District

On-site

INR 1,800,000 - 3,200,000

Full time

14 days+

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Job summary

Pmr Softtech in Chennai, India, seeks a Senior AI/ML Engineer to design and operate agentic systems using Amazon Bedrock, AgentCore, and RAG pipelines for automated claims processing.

You will work in an architect-led pod with data scientists and cloud architects, building scalable event-driven workflows, securing PHI data with KMS, and ensuring observability and compliance in HIPAA/SOC 2 environments. Strong Python and AWS skills are required.

Qualifications

  • Hands-on AI/ML design and development for agents, RAG, and event-driven pipelines in claims lifecycle.
  • Fluent in Python, comfortable with AWS serverless and container stacks, observability and security.

Responsibilities

  • Implements agents using Strands SDK on Bedrock AgentCore Runtime deployment, invocation, Memory, Identity, and Observability.
  • Designs and builds RAG architectures on Bedrock Knowledge Bases and vector stores for claims-domain semantics.
  • Builds MCP servers and downstream API aggregation.
  • Implements multi-agent orchestration patterns: sequential, parallel, and supervisor.
  • Instruments agents for tracing, monitoring, and debugging via AgentCore Observability.
  • Builds event-driven pipelines: async processing, Kafka producers/consumers, DLQs, and retry/backoff.
  • Manages claim state and audit trails in DynamoDB; handles PHI with KMS encryption and zero-trust IAM.

Skills

Python
AWS Bedrock
AgentCore Runtime
RAG
Event-driven pipelines
Lambda
FastAPI
Kafka
DynamoDB
IAM

Tools

Strands SDK
Bedrock AgentCore Runtime
MCP server

Job description

Senior AI/ML Engineer

Agentic AI Builder Bedrock AgentCore & Claims Automation

Experience:

  • 6+ yrs AI/ML design & development
  • 2+ yrs hands-on Agentic AI build

Role fit: Hands-on builder implementing agents, RAG, and event-driven pipelines for the automated claims lifecycle

Domain: Healthcare claims semantics; PHI-safe engineering under HIPAA / SOC 2

Works within: Architect-led pod alongside data scientists, cloud architects, and business analysts

PROFILE

Production-focused AI/ML engineer who builds and operates agentic systems, not just prototypes. Implements agents on Amazon Bedrock and AgentCore Runtime, stands up RAG over Bedrock Knowledge Bases, and wires them into event-driven AWS pipelines with the retry, DLQ, and audit patterns that regulated claims processing demands. Fluent in Python, comfortable across the AWS serverless and container stack, and disciplined about least-privilege security and observability.

WHAT THIS PERSON BUILDS ON THE ENGAGEMENT

Implements agents using Strands SDK (or equivalent) on Bedrock AgentCore Runtime deployment, invocation, Memory, Identity, and Observability

Designs and builds RAG architectures on Bedrock Knowledge Bases and vector stores, tuned for claims-domain semantics

Builds Model Context Protocol (MCP) servers and downstream API aggregation

Implements multi-agent orchestration patterns: sequential, parallel, and supervisor

Instruments agents for tracing, monitoring, and debugging via AgentCore Observability

Builds event-driven pipelines: async processing, Kafka producers/consumers, DLQs, and retry/backoff

Manages claim state and audit trails in DynamoDB; handles PHI with KMS encryption and zero-trust IAM

CORE TECHNICAL STRENGTHS
  • AI & agents Amazon Bedrock (model invocation, prompt engineering, RAG)
  • AgentCore Runtime (Memory, Identity, Observability, Gateway & Registry)
  • MCP server design
  • Healthcare/claims prompt design
  • Backend Python
  • FastAPI / REST integration
  • Kafka producers & consumers
  • Lambda functions
  • Strands agents
  • Event-driven Async pipelines
  • Dead-letter queues
  • Retry / backoff
  • SQS
  • EventBridge
  • Step Functions
  • Cloud & infra AWS (EKS, Lambda, S3, SQS, EventBridge, DynamoDB, Aurora RDS, CloudWatch)
  • Terraform
  • GitHub Actions CI/CD (dev test prod)
  • Data & compliance DynamoDB claim state + audit trail
  • S3
  • HIPAA / SOC 2 PHI patterns
  • KMS
  • Least-privilege IAM tied to AgentCore Identity

Preferred tooling Kiro spec-driven dev, agent code-gen, IaC generation, CI/CD scaffolding

ENGINEERING SIGNALS

Ships production-grade, observable agents with evaluation and guardrails baked in — not notebook demos

Comfortable owning a slice of the claims pipeline end to end and integrating it into the broader architecture

Security- and compliance-first by habit in a PHI environment

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