Lead/Staff Engineer - Applied AI in भारत

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead/Staff Engineer - Applied AI based in India. This is a high-autonomy engineering role focused on building LLM-powered AI agents and next-generation Generative AI systems at significant scale. You will lead the development of intelligent systems that power customer-facing automation, personalized communication, scheduling, and operational workflows. The role sits at the intersection of applied AI, agent architecture, data science, and production engineering. You will take ambitious ideas from research and experimentation through deployment, monitoring, and continuous iteration. The position offers the opportunity to work with large-scale data, retrieval systems, foundation models, and sophisticated agent architectures. You will collaborate closely with product, backend, infrastructure, and engineering teams to create reusable and scalable AI capabilities. As a technical leader, you will also influence AI strategy, establish best practices, and mentor engineers in a fast-moving, globally distributed environment. Accountabilities: - Architect, build, and deploy autonomous AI agents capable of executing complex workflows across sales, messaging, scheduling, and business operations. - Develop and fine-tune LLM solutions using both open-source models and API-based platforms, tailoring them to specific data, product, and customer requirements. - Design and scale robust Retrieval-Augmented Generation (RAG) systems and vector search infrastructure to support accurate, context-rich, real-time generation. - Develop and continuously refine prompt engineering, context construction, function calling, and agent tool-use strategies using LangChain or comparable orchestration frameworks.

- Apply advanced data science techniques, including predictive modeling, A/B testing, scoring, clustering, segmentation, causal inference, and time-series forecasting, to improve AI capabilities and broader product experiences. - Partner with backend, infrastructure, and product teams to develop reusable GenAI infrastructure covering model serving, prompt versioning, logging, evaluation systems, monitoring, and feedback loops. - Establish rigorous evaluation and experimentation processes to monitor agent performance, hallucination rates, reliability, and real-world effectiveness. - Lead initiatives from prototype through production, ensuring strong engineering practices, observability, scalability, and ongoing model improvement. - Influence the AI roadmap and technical direction while mentoring engineers and contributing to engineering standards, architecture decisions, and best practices. - Translate technical possibilities and constraints into practical product solutions while maintaining a strong focus on customer and business outcomes. Requirements: - 8+ years of experience in Data Science, Machine Learning, Applied AI, or a closely related field, with a demonstrated history of delivering production-grade AI and ML systems. - Hands-on expertise with LLM technologies, including fine-tuning, prompt engineering, embeddings, function-calling agents, and model evaluation. - Strong experience designing and implementing RAG systems using vector databases such as FAISS, Pinecone, or Weaviate. - Experience working in cloud-native environments, particularly GCP and AWS, with experience deploying models using technologies such as PyTorch, Hugging Face Transformers, and MLOps tooling. - Experience with LangChain or similar agent orchestration frameworks, including the ability to design multi-step, tool-augmented agents. - Strong Python programming skills combined with sound engineering practices around CI/CD, testing, version control, and production software development; familiarity with TypeScript is also valuable.