Generative Ai Engineer

3 days ago

Bareilly, India Whatjobs IN C2 Full time

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.

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