Grid Dynamics - Lead AI Engineer - RAG/LLM

Description :

As a Lead AI Engineer, you will be responsible for architecting sophisticated multi-agent systems and optimizing RAG pipelines on our LightSpeed Enterprise platform.

Role Overview :

- Experience : 7 to 13 Years

- Location : Chennai (On-site)

- Notice Period : Immediate to 15 Days (Mandatory)

- Selection Process : Final Level discussion will be a Face-to-Face interview (Mandatory).

Technical Stack & Responsibilities :

1. Large Language Models (LLMs) & Orchestration :

- Production Deployment : Hands-on experience deploying and scaling applications using Gemini, Claude, and OpenAI.

- Complex Orchestration : Expert-level proficiency with LangChain and LlamaIndex.

- Agentic Workflows : Designing and implementing autonomous multi-agent systems using LangGraph to handle complex, non-linear reasoning tasks.

2. Machine Learning & Deep Learning :

- Frameworks : Mastery of PyTorch or TensorFlow for building and training neural networks.

- Fine-tuning : Proven track record of fine-tuning LLMs (PEFT, LoRA, QLoRA) to improve performance on domain-specific tasks.

3. Advanced RAG & Data Engineering :

- Vector Ecosystems : Implementation of high-performance Vector Databases (e.g., Pinecone, Weaviate, or Milvus).

- Data Architecture : Managing structured and unstructured data using PostgreSQL and advanced retrieval-augmented generation (RAG) techniques.

- Search Optimization : Implementing hybrid search, reranking, and query transformation strategies.

4. MLOps & Infrastructure :

- Containerization : Robust experience with Docker for environment consistency.

- Orchestration : Deploying and managing workloads on OpenShift.

- Production Monitoring : Setting up evaluators, tracing, and monitoring for LLM outputs to ensure reliability and safety.

Key Qualifications :

- Platform Experience : Prior experience or the ability to quickly master the LightSpeed Enterprise platform.

- Architectural Mindset : Ability to design end-to-end AI systems from data ingestion to production APIs.

- Mentorship : Ability to lead junior engineers and conduct rigorous code/architecture reviews.

- Communication : Strong interpersonal skills to explain complex AI concepts to stakeholders.