Sr. AI ML Engineer

Connected Value Health Solutions; Chennai District, Coimbatore District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Connected Value Health Solutions seeks a Senior AI/ML Engineer to design, build and deploy production-grade AI solutions for healthcare and enterprise use cases. The role emphasizes Gen AI, LLMs, SLMs, RAG, and agentic workflows across product teams.

You will collaborate with product managers, healthcare SMEs and engineers to deliver scalable, secure and measurable AI products with strong governance and cost controls.

Qualifications

• 6+ years of experience in AI/ML or software engineering.

Responsibilities

• Design, build and deploy production-grade AI/ML/Generative AI solutions.
• Develop agentic workflows with multi-agent orchestration and tool calls.
• Create scalable APIs and microservices for AI-powered products.
• Mentor junior engineers and contribute to engineering standards.

Skills

Python

LLMs

RAG pipelines

AI orchestration

REST APIs

Docker

CI/CD

Cloud platforms

Education

Bachelor's or Master's in CS/AI/Engineering

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

OpenAI/Azure OpenAI/AWS Bedrock

Pinecone/Weaviate/FAISS

Job description

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

Experience: 6-8+ 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

• 48+ 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 data‑handling 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 shouldor should notbe 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

• Bachelors or Masters 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.