Bengaluru, Karnataka
Job Summary

10+ years (min. 2 years in GenAI / LLM systems)

We are seeking a Senior AI/ML Engineer to design, develop, and deploy production-grade AI/ML solutions within GSK’s Digital & Tech organization. This role focuses on building Generative AI applications, multi-agent systems, and advanced retrieval pipelines that drive measurable business impact. You will work at the intersection of cutting-edge AI research and enterprise software engineering, collaborating with data scientists, platform engineers, and domain experts across R&D;, supply chain, and commercial functions.

Key Responsibilities

Generative AI & LLM Development

Design, develop, and deploy Generative AI applications using LLMs (GPT-4, Claude, Gemini, open-source models) for enterprise use cases
Build and orchestrate multi-agent systems using frameworks like LangGraph, LangChain, CrewAI, or AutoGen with function calling and tool use
Implement Retrieval-Augmented Generation (RAG), Graph RAG, and hybrid retrieval pipelines using vector databases (Pinecone, Weaviate, Chroma, pgvector)
Apply prompt engineering, chain-of-thought reasoning, and context engineering techniques to optimize model outputs
Fine-tune LLMs and embedding models for domain-specific tasks using LoRA, QLoRA, or full fine-tuning approaches
Implement guardrails, content filtering, and safety mechanisms for responsible AI deployment

ML Engineering & MLOps

Build end-to-end ML pipelines – data ingestion, feature engineering, model training, evaluation, and deployment
Implement LLMOps practices: model versioning, A/B testing, prompt management, evaluation frameworks (LLM-as-judge, RAGAS, custom metrics)
Deploy and manage LLM inference using frameworks such as vLLM, TensorRT-LLM, or DeepSpeed for latency and cost optimization
Monitor model performance, detect drift, and implement continuous improvement loops
Build observability for AI systems using LangSmith, Langfuse, or custom tracing solutions





Architecture & Cloud

Architect scalable AI solutions on AWS (Bedrock, SageMaker, Lambda) or Azure (OpenAI Service, ML Studio)
Containerize AI applications with Docker and deploy via Kubernetes, ECS, or serverless patterns
Design event-driven and API-first architectures for AI service integration with enterprise systems
Implement CI/CD pipelines for ML models and AI applications

Collaboration & Leadership

Collaborate with data scientists, domain experts, and product owners to translate business problems into AI solutions
Conduct code reviews, architectural design reviews, and contribute to engineering standards
Mentor junior AI/ML engineers; lead technical knowledge-sharing sessions
Evaluate and recommend emerging AI technologies, frameworks, and approaches
Present AI solutions and results to technical and non-technical stakeholders
Skill Requirements

Skill Area

Required Proficiency / Technologies

GenAI & LLMs

LangChain, LangGraph, OpenAI API, Claude API, Hugging Face Transformers, prompt engineering, multi-agent orchestration

ML Frameworks

PyTorch, TensorFlow, Scikit-learn, XGBoost; fine-tuning (LoRA / QLoRA / PEFT)

NLP & Retrieval

RAG, Graph RAG, hybrid search, vector DBs (Pinecone, Weaviate, Chroma), embedding models, NER, text classification

LLMOps & Eval

LangSmith, Langfuse, RAGAS, LLM-as-judge, model versioning, A/B testing, prompt management

Inference

vLLM, TensorRT-LLM, DeepSpeed, ONNX Runtime, quantization techniques

Cloud & Infra

AWS (Bedrock, SageMaker, Lambda, S3) or Azure; Docker, Kubernetes, Terraform

Programming

Python (primary), FastAPI, SQL, Git, Bash; familiarity with TypeScript / JavaScript a plus

Data & Tools

PostgreSQL, Neo4j, MongoDB, Redis, Apache Kafka, Databricks, Jupyter, MLflow

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📌 Senior Technical Lead (India)
🏢 HCLTech
📍 India