Technical Lead/ Technical BA - AI

Job Description:

We are looking for an experienced AI Practice Lead with strong AI literacy and proven expertise in designing, implementing, and integrating AI agents into enterprise systems. This role will lead the organization's AI strategy, build scalable AI capabilities, and drive real-world adoption of agentic AI solutions that deliver measurable business impact.

Key Responsibilities:

AI Strategy & Practice Leadership Define and execute the AI practice vision, roadmap, and operating model. Identify, evaluate, and prioritize AI agent use cases across business functions. Establish AI standards, governance, security, and responsible AI practices. Build repeatable frameworks for AI agent design, orchestration, and deployment. AI Agent Design & Implementation Lead the design and development of AI agents using LLMs and agentic frameworks. Implement multi-agent systems, tool-using agents, and workflow orchestration. Integrate AI agents with enterprise systems (APIs, databases, CRMs, ERPs, data platforms). Oversee prompt engineering, RAG architectures, fine-tuning, and evaluation. Ensure reliability, observability, and performance of AI agents in production. Delivery & Architecture Own end-to-end delivery of AI solutions, from PoC to production. Define reference architectures for agent-based AI, GenAI, and MLOps. Ensure scalability, security, and compliance of AI solutions. Review solution designs and provide technical direction to teams. Client Engagement & Pre-Sales Act as a trusted advisor to stakeholders on AI transformation and agent adoption. Lead AI workshops, discovery sessions, and agent-based PoCs. Support proposals, RFPs, and solution presentations with strong AI storytelling. Team Building & Enablement Build, mentor, and lead AI engineers, data scientists, and platform teams. Upskill teams on AI literacy, agent frameworks, and best practices. Drive innovation, experimentation, and continuous learning across the practice.

Required Skills & Qualifications:

12+ years of experience in AI, ML, Data, or Advanced Analytics, with leadership experience. Strong AI literacy, including understanding of LLMs, GenAI, and agentic systems. Proven hands-on experience in creating, implementing, and integrating AI agents. Experience with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.). Strong understanding of RAG, vector databases, embeddings, and evaluation metrics. Experience integrating AI agents with enterprise APIs and workflows. Proficiency with cloud AI platforms (AWS, Azure, GCP). Solid understanding of security, privacy, and responsible AI. Good to

Have:

Experience setting up an AI Center of Excellence (CoE). Knowledge of MLOps / LLMOps tools and practices. Experience with multi-agent orchestration and workflow engines. Consulting or client-facing experience. Advanced degree in Computer Science, AI, or Data Science.