AI Tech Lead

Job Description Supplier.io is the market leader in supplier intelligence, trusted by over half of the Fortune 100 to power smarter, more responsible sourcing decisions. Our platform helps corporate procurement teams discover, evaluate, and engage with over 11 million suppliers with a focus on local, small, diverse, and sustainable businesses. This helps organizations build supply chains that are resilient, inclusive, and built for impact. Our solutions empower today's procurement teams with accurate data, actionable insights, and measurable impact, which helps them mitigate risk, expand sourcing options, achieve ESG goals, and advance economic inclusion. Whether tracking spend, sourcing alternate suppliers, or measuring program results, Supplier.io transforms complexity into clarity; empowering teams to lead with confidence and build supply chains that deliver for both business and community. Join a company committed to innovation, inclusion, and making a difference one sourcing decision at a time. For more information, visit www.supplier.io. Reports to: CTO Number of Direct Reports: N/A Location: Hyderabad, India Working Shift: UK/Hybrid (2 days a week at office) The Opportunity We are at an exciting stage in our AI journey. Supplier.io is embedding advanced AI capabilities across its data and product ecosystem to accelerate innovation and deliver smarter, more personalized sourcing experiences. The AI Technical Lead will serve as the CTO's right hand in designing, developing, and implementing AI solutions that power Supplier.io's next-generation platform. This is a hands-on individual contributor role focused on deep technical expertise, architecture, and execution, not people management. The ideal candidate will bring strong experience with LLM architecture, RAG systems, and agentic frameworks alongside a solid foundation in machine learning and data engineering. What You Will Do - AI Architecture & System Design - Architect, prototype, and deploy large language model (LLM) and retrieval-augmented generation (RAG) systems that enhance Supplier.io products. - Design scalable architectures for integrating LLMs into production workflowsbalancing cost, latency, and performance. - Develop agentic AI workflows to automate complex tasks such as supplier search, enrichment, classification, and insights generation. - Collaboration & Leadership - Partner closely with AI Engineers to define implementation details, guide development, and ensure code quality and performance. - Collaborate with Product Managers and the CTO to translate business objectives into robust AI technical solutions. - Establish best practices for model orchestration, evaluation, and continuous improvement. - Research & Innovation - Explore emerging frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, etc.) and assess their applicability to Supplier.io use cases. - Prototype, benchmark, and refine LLM-driven components for semantic search, summarization, supplier matching, and recommendation systems. - Drive experimentation to evaluate open-source and proprietary LLMs, embeddings, and vector databases (e.g., Pinecone, Chroma, Weaviate). - Operational Excellence - Define observability, testing, and deployment standards for AI components across environments. - Work with DevOps and Data Engineering to optimize pipelines for scalability and cost efficiency. - Contribute to model governance, documentation, and reproducibility practices. - Security, Privacy & Compliance - Ensure all LLM and RAG implementations follow security best practices related to data confidentiality, PII handling, and prompt injection prevention. - Partner with Legal/Security to ensure compliance with SOC 2, GDPR, and other relevant standards. - AI Roadmap & Strategy Contribution - Contribute to the annual AI roadmap by proposing scalable LLM-powered features, tools, and platform investments. Evaluate build-vs-buy decisions for vendor AI tools and foundational models. What You Will Bring - 7+ years of experience in AI/ML engineering, with 3+ years of recent focus on LLM, NLP, or RAG-based architectures. - Proven experience designing and deploying AI systems in production using frameworks like LangChain, LlamaIndex, Hugging Face, or Ray. - Strong understanding of LLM architecture, embeddings, fine-tuning, and inference optimization. - Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn). - Experience with vector databases (Pinecone, Chroma, FAISS, Weaviate) and cloud platforms (GCP, AWS, or Azure). - Familiarity with agentic AI frameworks and multi-agent orchestration concepts. - Working knowledge of MLOps, model evaluation, and continuous delivery pipelines. - Excellent collaboration and communication skills with the ability to influence technical direction across teams. Why Join Supplier.io - Collaborate directly with the CTO on shaping and executing the company's AI roadmap. - Work on real-world AI systems powering the leading supplier intelligence platform trusted by global enterprises. - Build and ship production-grade AI features that impact procurement and sourcing outcomes at scale. - Be part of a fast-moving, innovation-driven culture that values creativity, ownership, and results.