Job Description
We are looking for a Lead AI Engineer who can design, build, and scale end-to-end AI systems, combining solid 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

📌 Lead AI Engineer (India)
🏢 Ensylon
📍 India