About the role
We are looking for an experiencedAIPracticeLead with strongAIliteracy and proven expertise in designing, implementing, and integratingAIagents into enterprise systems. This role will lead the organization’sAIstrategy, build scalableAIcapabilities, and drive real-world adoption of agenticAIsolutions that deliver measurable business impact.
Key Responsibilities:
AIStrategy &PracticeLeadership
- Define and execute theAIpracticevision, roadmap, and operating model.
- Identify, evaluate, and prioritizeAIagent use cases across business functions.
- EstablishAIstandards, governance, security, and responsibleAIpractices.
- Build repeatable frameworks forAIagent design, orchestration, and deployment.
- Lead the design and development ofAIagents using LLMs and agentic frameworks.
- Implement multi-agent systems, tool-using agents, and workflow orchestration.
- IntegrateAIagents with enterprise systems (APIs, databases, CRMs, ERPs, data platforms).
- Oversee prompt engineering, RAG architectures, fine-tuning, and evaluation.
- Ensure reliability, observability, and performance ofAIagents in production.
- Own end-to-end delivery ofAIsolutions, from PoC to production.
- Define reference architectures for agent-basedAI, GenAI, and MLOps.
- Ensure scalability, security, and compliance ofAIsolutions.
- Review solution designs and provide technical direction to teams.
- Act as a trusted advisor to stakeholders onAItransformation and agent adoption.
- LeadAIworkshops, discovery sessions, and agent-based PoCs.
- Support proposals, RFPs, and solution presentations with strongAIstorytelling.
- Build, mentor, and leadAIengineers, data scientists, and platform teams.
- Upskill teams onAIliteracy, agent frameworks, and best practices.
- Drive innovation, experimentation, and continuous learning across thepractice.
12+ years of experience inAI, ML, Data, or Advanced Analytics, with leadership experience.StrongAIliteracy, including understanding of LLMs, GenAI, and agentic systems.
Proven hands-on experience in creating, implementing, and integratingAIagents.
Experience with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.).
Strong understanding of RAG, vector databases, embeddings, and evaluation metrics.
Experience integratingAIagents with enterprise APIs and workflows.
Solid understanding of security, privacy, and responsibleAI.
Good to Have:
- Experience setting up anAICenter 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.