Lead AI Engineer

Job DescriptionWe 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 ResponsibilitiesCore AI/ML Engineering (Traditional AI)Design and develop ML/DL models from scratch for real-world problemsHandle full lifecycle: data → training → evaluation → deployment → monitoringWork with structured/unstructured data, feature engineering, and model optimizationBuild scalable ML pipelines with reproducibility and versioningGenerative AI & LLM SystemsBuild 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 optimizationWork with multi-model setups (OpenAI, Claude, open-source LLMs, Bedrock, etc.)Agentic Systems & Advanced ArchitecturesDesign 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 reasoningSystem Design & ProductionizationArchitect scalable AI systems for enterprise use casesBuild APIs and microservices for AI solutionsEnsure: (Low latency, High reliability, Cost optimization)Work with Docker, Kubernetes, CI/CD pipelinesObservability, Evaluation & ReliabilityImplement monitoring, logging, and tracing (e.g., Langfuse, Prometheus)Define evaluation frameworks: (Accuracy, Retrieval quality, Hallucination detection)Debug across: (Model, Data, Retrieval, System Layers)Collaboration & OwnershipWork directly with AI Lead / CTO / Product teamsTranslate business problems into AI solutionsOwn delivery of POCs → production systemsLead and mentor a small team and guide them on best practicesWork independently on AI/ML projects and contribute to end-to-end delivery.Required Skills & ExperienceExperience6–9 years of experience in AI/ML and Gen-AI systems with strong exposure to software engineeringTechnical SkillsStrong programming: Python (mandatory)ML/DL frameworks: PyTorch / TensorFlow / Scikit-learnLLM frameworks: LangChain / LlamaIndex / LangGraph (preferred)Vector DBs: FAISS / Pinecone / Weaviate / OpenSearchCloud: AWS / Azure / GCP (Bedrock / Azure OpenAI preferred)APIs: FastAPI / FlaskDevOps: Docker, Kubernetes, CI/CDCore CompetenciesStrong understanding of:ML fundamentals (bias/variance, optimization)NLP and embeddingsRetrieval systemsAbility to debug end-to-end AI systemsExperience in production deployment and scalingStrong system design and problem-solving skillsGood to HaveExperience with:Multi-agent systemsReinforcement learningKnowledge graphs + RAGExperience working with large-scale datasetsExposure to AI safety, governance, and complianceWhat We ExpectAbility to build systems from scratch (not just use APIs)Strong ownership mindset (end-to-end responsibility)Ability to handle evolving requirementsPassion to stay updated with latest AI advancements