Generative AI Engineer(LLMs & RAG)-Healthcare SaaS

Generative AI Engineer (LLMs & RAG) Healthcare SaaS

Location:

About the Role

hands-on Generative AI Engineer

Generative AI and healthcare innovation

Key Responsibilities

• Architect and optimize RAG pipelines

  ingestion, embedding, retrieval, grounding, and generation.

• Experiment with LLMs

  open-weight models (LLaMA, Mistral, Falcon) and API-based models (OpenAI, Anthropic).

• Implement evaluation & monitoring frameworks

  (retrieval precision, grounding accuracy, hallucination checks, latency, safety).

• Work with diverse healthcare datasets

  PDFs, EHR/EMR data, CSVs, structured knowledge bases.

• Deploy AI services to cloud-native environments

  (AWS, GCP, or Azure) with observability and security in mind.

• Collaborate cross-functionally

  with product, clinicians, DevOps, and QA to ship production-ready features.

Must-Have Skills

• 5+ years of experience in software/ML engineering with strong Python skills (backend + API development).
• Proven expertise building

  LLM-powered applications and RAG pipelines

  .
• Strong understanding of embeddings, transformers, prompt engineering/orchestration, and NLP techniques.
• Hands-on experience with vector databases (FAISS, Pinecone, Qdrant, Weaviate, Milvus).
• Familiarity with LangChain, LLMOps, and ML deployment workflows.
• Experience with containerized deployments (Docker/Kubernetes) and cloud platforms.
• Exposure to both

  open-weight LLMs

  and

  hosted APIs

  .

Nice to Have

• Experience in healthcare/healthtech; knowledge of HIPAA-compliant systems.
• Familiarity with

  autonomous agent frameworks

  (LangGraph, AutoGen, CrewAI).
• Understanding of clinical NLP ontologies (SNOMED CT, ICD, UMLS).
• Contributions to open-source AI/ML projects or published proofs-of-concept.
• Experience building real-time SaaS applications powered by AI.
• Exposure to multimodal retrieval (structured + unstructured data, including medical images).

Soft Skills & Expectations

• Bias for action: eager to prototype fast while caring about reliability in a healthcare context.
• Clear communicator who documents clean code and shares progress proactively.
• Comfortable working independently in an

  ambiguous, fast-paced startup environment

  .
• Flexible for early/late standups with global teams.

What We Offer

• Opportunity to

  shape one of the first LLM-powered healthcare copilots

  at scale.
• Autonomy, trust, and ownership in a results-driven team.
• Direct mentorship from senior AI researchers and clinicians.
• Chance to publish technical blogs or papers on healthcare AI.
• Flexible remote setup with a Hyderabad base.
• Competitive salary with performance bonuses.

How to apply

send your updated resume to:

Primary email:

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