Lead AI Engineer

Job Description
We are looking for a Lead AI Engineer who can design, build, and scale end-to-end AI systems, combining strong foundations in Machine Learning/Deep Learning with hands-on experience in Generative AI (LLMs, RAG, Agentic systems).
This role requires someone who can own problems from idea to production, work closely with leadership, and contribute to building enterprise-grade AI platforms.
Key Responsibilities
Core AI/ML Engineering (Traditional AI)
Design and develop ML/DL models from scratch for real-world problems
Handle full lifecycle: data → training → evaluation → deployment → monitoring
Work with structured/unstructured data, feature engineering, and model optimization
Build scalable ML pipelines with reproducibility and versioning
Generative AI & LLM Systems
Build and deploy LLM-powered applications (chatbots, copilots, assistants, etc.,)
Design and implement RAG pipelines: (Document ingestion, chunking, embeddings, Vector search (FAISS, Pinecone, etc.), Retrieval optimization)
Implement prompt engineering, evaluation, and optimization
Work with multi-model setups (OpenAI, Claude, open-source LLMs, Bedrock, etc.)
Agentic Systems & Advanced Architectures
Design and build AI Agents / Agentic workflows (LangGraph, Langsmith/crewAI, etc.)
Implement (Tool calling, Planning & reasoning workflows, multi-step decision pipelines)
Optimize systems for long-horizon tasks and complex reasoning
System Design & Productionization
Architect scalable AI systems for enterprise use cases
Build APIs and microservices for AI solutions
Ensure: (Low latency, High reliability, Cost optimization)
Work with Docker, Kubernetes, CI/CD pipelines
Observability, Evaluation & Reliability
Implement monitoring, logging, and tracing (e.g., Langfuse, Prometheus)
Define evaluation frameworks: (Accuracy, Retrieval quality, Hallucination detection)
Debug across: (Model, Data, Retrieval, System Layers)
Collaboration & Ownership
Work directly with AI Lead / CTO / Product teams
Translate business problems into AI solutions
Own delivery of POCs → production systems
Lead and mentor a small team and guide them on best practices
Work independently on AI/ML projects and contribute to end-to-end delivery.
Required Skills & Experience
Experience
6–9 years of experience in AI/ML and Gen-AI systems with strong exposure to software engineering
Technical Skills
Strong programming: Python (mandatory)
ML/DL frameworks: PyTorch / TensorFlow / Scikit-learn
LLM frameworks: LangChain / LlamaIndex / LangGraph (preferred)
Vector DBs: FAISS / Pinecone / Weaviate / OpenSearch
Cloud: AWS / Azure / GCP (Bedrock / Azure OpenAI preferred)
APIs: FastAPI / Flask
DevOps: Docker, Kubernetes, CI/CD
Core Competencies
Strong understanding of:
ML fundamentals (bias/variance, optimization)
NLP and embeddings
Retrieval systems
Ability to debug end-to-end AI systems
Experience in production deployment and scaling
Strong system design and problem-solving skills
Good to Have
Experience with:
Multi-agent systems
Reinforcement learning
Knowledge graphs + RAG
Experience working with large-scale datasets
Exposure to AI safety, governance, and compliance
What We Expect
Ability to build systems from scratch (not just use APIs)
Strong ownership mindset (end-to-end responsibility)
Ability to handle evolving requirements
Passion to stay updated with latest AI advancements

Work arrangement
No