Associate AI Engineer

7 days ago

Bengaluru, Karnataka, India Claimsync Full time ₹ 20,00,000 - ₹ 25,00,000 per year

We're building the future of healthcare automation — starting with the 
post-acute, value-based care space
, where both medication overload and revenue cycle complexity are driving unnecessary costs and poor outcomes. Founded by Dev Roy (2x exited founder), our stealth start-up is building 
multi-agent LLM systems
 that operate with 
transparency, accuracy, and traceability
 — tackling two of the hardest problems in the healthcare stack: 
medication optimization
 and 
revenue cycle management (RCM)
.

We use 
LangGraph
 and a tightly structured 
MCP (Model-Context-Protocol)
 architecture — where agents don't just generate text, but operate over 
stateful contexts
, issue 
tool calls
, and follow 
explicit protocol-guided reasoning loops
. The agents we build don't guess — they explain, document, and prove.

Responsibilities

  • Architect and implement 
    multi-agent systems
     using LangGraph, leveraging an 
    MCP-inspired structure
    : agents with memory, contextual tool use, and protocol-defined responsibilities
  • Build workflows that replicate expert-level medical coding and medication review processes
  • Design tool interfaces (e.g. vector DB, ICD-10 knowledge graph, FHIR endpoints) and integrate them into agents' decision-making loops
  • Orchestrate LLM calls with clear traceability, structured state, and logging for regulatory-grade auditability
  • Own experiments and iterate rapidly to improve reasoning, accuracy, and output alignment
  • Collaborate closely with the founder on roadmap, architecture, and product direction

Qualifications

  • 1+ years of experience in AI/ML, NLP, or backend system design
  • Strong Python engineering fundamentals and practical experience with 
    LangGraph
    , 
    LangChain
    , or similar agent frameworks
  • Comfortable building 
    MCP-style architectures
     — where agents reason with structured inputs, manage context, and follow execution protocols
  • Experience with 
    LLM APIs
     (OpenAI, Anthropic, Claude), prompt engineering, and managing token/latency trade-offs
  • Familiarity with 
    vector search engines
     (Pinecone, Chroma, Weaviate) and 
    RAG-based retrieval systems
  • Bonus: background in 
    clinical NLP
    , 
    medical coding standards
     (ICD-10, CPT), or exposure to 
    FHIR/HL7
  • Startup mindset: autonomous, fast-moving, curious, and deeply pragmatic

If you want to build 
human-grade AI agents
 that actually matter — not chatbots, but reasoning systems that impact clinical decisions and billing integrity — we'd love to talk.

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