Sr AI/ML Engineer

Senior AI/ML Engineer – Generative AI, LLMs & Agentic AI

Experience: 4–8+ years

Location: [Chennai/Coimbatore]

Employment Type: Full-time

Industry: Healthcare Technology / Artificial Intelligence

About the Role

We are looking for a hands-on Senior AI/ML Engineer to design, build and launch 

production-grade AI solutions for healthcare and enterprise use cases.

The ideal candidate will have strong experience in Machine Learning, Generative 

AI, Large Language Models, Small Language Models, Retrieval-Augmented 

Generation and Agentic AI systems. You should be able to take a business 

problem from discovery and solution design through development, deployment, 

launch and continuous improvement.

This is not a research-only or proof-of-concept role. You will work closely with 

Product Managers, Business Analysts, healthcare SMEs, architects and engineering 

teams to build AI products that are scalable, secure, measurable and commercially 

valuable.

Key Responsibilities

• Design, develop and deploy AI/ML and Generative AI solutions from concept 

to production.

• Build applications using LLMs, SLMs, RAG, GraphRAG, AI agents, NLP and 

machine-learning models.

• Develop agentic workflows involving tool calling, planning, memory, routing, 

human-in-the-loop controls and multi-agent orchestration.

• Build and optimize retrieval pipelines using embeddings, semantic search, 

hybrid search, vector databases, reranking and metadata filtering.

• Integrate AI solutions with enterprise platforms, databases, APIs, healthcare 

systems and third-party applications.

• Evaluate and select the right approach across traditional ML, LLMs, SLMs, 

prompt engineering, fine-tuning, RAG and deterministic workflows.

• Build evaluation frameworks to measure accuracy, groundedness, 

hallucination, retrieval relevance, latency, safety and cost.

• Implement AI guardrails, structured outputs, confidence scoring, fallback 

mechanisms and auditability.

• Create scalable APIs and microservices for AI-powered products.

• Implement MLOps and LLMOps practices, including model and prompt 

versioning, monitoring, tracing, CI/CD and production observability.

• Optimize model performance, token consumption, inference cost, response 

time and infrastructure usage.

• Translate business requirements into technical solutions, architecture, 

delivery plans and measurable outcomes.

• Participate in product discovery, customer discussions, technical 

demonstrations and solution reviews.

• Mentor junior engineers and contribute to AI engineering standards and 

reusable frameworks.

Required Skills and Experience

• 4–8+ years of experience in AI/ML, data science, applied machine learning or 

software engineering.

• Strong programming experience in Python with production-quality coding 

practices.

• Hands-on experience building and deploying applications using LLMs or 

Generative AI models.

• Practical experience with RAG pipelines, AI agents, prompt engineering, 

embeddings and vector search.

• Strong understanding of machine learning, deep learning, NLP, model 

evaluation and data processing.

• Experience with AI orchestration frameworks such as LangChain, 

LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI or 

equivalent.

• Experience with model platforms such as OpenAI, Azure OpenAI, Anthropic 

Claude, AWS Bedrock, Google Vertex AI, Hugging Face, Llama or Mistral.

• Experience with vector databases or search platforms such as Pinecone, 

Weaviate, Qdrant, Milvus, FAISS, pgvector, Elasticsearch or OpenSearch.

• Experience developing REST APIs and microservices using FastAPI, Flask or 

similar frameworks.

• Experience with SQL, relational databases and structured and unstructured 

data processing.

• Experience deploying applications on AWS, Microsoft Azure or Google 

Cloud Platform.

• Working knowledge of Docker, Git, automated testing and CI/CD.

• Understanding of AI security, privacy, scalability, monitoring, latency and 

cost optimization.

• Proven experience taking at least one AI/ML product or solution from 

inception to production launch.

• Strong problem-solving, critical-thinking and stakeholder communication 

skills.

Preferred Skills

• Experience in healthcare, life sciences, pharmaceuticals, payer, provider or 

patient-support solutions.

• Understanding of healthcare workflows such as patient engagement, prior 

authorization, benefits verification, clinical documentation, claims or 

pharmacovigilance.

• Familiarity with FHIR, HL7, EHR/EMR integrations, HIPAA and PHI datahandling requirements.

• Experience with Small Language Models, model fine-tuning, quantization or 

open-source model deployment.

• Experience with NVIDIA AI technologies, GPU inference or model 

optimization.

• Experience with multimodal AI involving documents, voice, audio, images or 

conversational interfaces.

• Experience working in a startup, product organization or customer-facing 

solution engineering environment.

• Knowledge of responsible AI, model governance, bias management and 

explainability.

What We Are Looking For

• A builder who can convert ambiguous problems into working AI products.

• A product-minded engineer who understands both technical feasibility and 

business value.

• Someone who can challenge assumptions and recommend when AI 

should—or should not—be used.

• A strong collaborator who can work effectively with Product, Business, 

Engineering and healthcare teams.

• A practical problem solver who takes ownership from solution design 

through production launch.

• Someone who continuously learns and adapts as AI technologies evolve.

Why Join Us?

• Build real-world healthcare AI products with measurable business impact.

• Work across LLMs, SLMs, RAG, Agentic AI, multimodal AI and intelligent 

automation.

• Own solutions across the complete lifecycle—from discovery to launch.

• Influence AI architecture, product direction and engineering standards.

• Work in a fast-moving environment where your ideas and technical decisions 

directly shape products.

Education

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine 

Learning, Data Science, Engineering or a related discipline.

Equivalent hands-on experience with a strong record of delivering production AI 

solutions will also be considered.