Role Summary

We are looking for a Senior Data / ML Engineer with 6+ years of experience to design, build, and productionize GenAI, LLM, RAG, and agentic AI solutions. The role is highly hands-on and focused on developing scalable, reliable, and enterprise-ready AI systems that solve real-world business problems.

Roles Responsibilities

- Design and develop LLM-powered applications and agentic AI workflows, including single-agent and multi-agent systems.
- Build scalable RAG pipelines using embeddings, vector databases, retrieval, and prompt optimization techniques.
- Develop end-to-end ML/LLM pipelines covering data ingestion, processing, model integration, inference, deployment, and monitoring.
- Productionize AI solutions with observability, guardrails, security, reliability, and cost/performance optimization.
- Integrate GenAI and ML solutions with enterprise applications, platforms, APIs, and business workflows.
- Implement MLOps practices for model/pipeline monitoring, deployment, versioning, and operational reliability.
- Collaborate with product, engineering,



platform, and governance teams to deliver scalable and responsible AI solutions.

Required Skills

- 6+ years of experience in Data Engineering, ML Engineering, Applied AI, or a related field.
- Solid hands-on experience with Python and scalable data/AI systems.
- Proven experience building and deploying LLM/GenAI applications in production.
- Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and LLM application development.
- Experience with agentic AI frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar.
- Good understanding of ML/LLM pipelines, MLOps, monitoring, deployment, and performance optimization.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Analyst - Data Science (Chennai)
🏢 Latentview
📍 Chennai