Job Title

About the RoleWe are seeking a visionary and technically astuteLead AI Architectto lead the architecture and design of scalable AI systems and next-generation intelligent platforms. As a core member of the leadership team, you will be responsible for driving end-to-end architectural strategy, model optimization, and AI infrastructure that powers mission-critical solutions across our product lines. This is afoundational rolefor someone passionate about architecting solutions involvingRAG ,SLMs/LLMs ,multi-agent systems , and scalable model pipelines across cloud-native environments. Salary30 - 45 LPA with additional benefits. Key ResponsibilitiesDefine and own theAI/ML architectural roadmap , aligning with product vision and technical goals. Architect and oversee implementation ofRAG-based solutions ,LLM/SLM fine-tuning pipelines , andmulti-agent orchestration . Lead design of model training and inference pipelines ensuring scalability, modularity, and observability. Evaluate and select open-source and proprietary foundation models for fine-tuning, instruction tuning, and domain adaptation. Guide integration of vector databases, semantic search, and prompt orchestration frameworks (LangChain, LlamaIndex, etc.). Ensure best practices inmodel deployment, versioning, monitoring , and performance optimization (GPU utilization, memory efficiency, etc.). Collaborate with Engineering, DevOps, Product, and Data Science teams to bring AI features to production. Mentor mid-level engineers and interns; contribute totechnical leadershipandcode quality . Maintain awareness of latest research, model capabilities, and trends in AI. Required Skills & Qualifications6+ years of hands-on experience in AI/ML architecture and model deployment. Expert-level knowledge of Python and libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and FastAPI. Deep understanding of LLMs/SLMs, embedding models, tokenization strategies, fine-tuning, quantization, and LoRA/QLoRA. Proven experience withRetrieval-Augmented Generation (RAG)pipelines and vector DBs like FAISS, Pinecone, or Weaviate. Strong grasp of system design, distributed training, MLOps, and scalable cloud-based infrastructure (AWS/GCP/Azure). Experience with containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLFlow, W&B). Experience in building secure and performantREST APIs , deploying and monitoring AI services in production. Nice to HaveExposure to multi-agent frameworks, task planners, or LangGraph. Experience leading AI platform teams or architecting enterprise-scale ML platforms. Familiarity with Data Governance, Responsible AI, and model compliance requirements. Published papers, open-source contributions, or patents in the AI/ML domain. Why Join UsBe at the forefront of innovation in AI and language intelligence. Influence strategic technical decisions and drive company-wide AI architecture. Lead a growing AI team in a high-impact, fast-paced environment. Competitive compensation, equity options, and leadership opportunity.