
Generative AI Engineer(LLMs
7 days ago
Generative AI Engineer (LLMs & RAG) Healthcare SaaS
Location: Remote / Hyderabad (preferred)
Experience: 5+ years
Employment Type: Full-time
Domain: Generative AI, Healthcare, SaaS
About the Role
We are looking for a hands-on Generative AI Engineer with expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). In this role, you will architect and deliver production-grade AI systems that combine unstructured and structured healthcare data to power a next-generation clinical assistant.
You will work at the cutting edge of Generative AI and healthcare innovation, helping design safe, scalable, and impactful solutions that directly influence real-world patient outcomes. This is a chance to take ownership of core AI systems in a fast-moving, high-impact product.
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
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