Agentic AI Lead

Required:

·         Overall 12+ years of IT industry experience.

·         Education:  B.S. or M.S. in Computer Science, AI, or a related field is preferred.

·         Experience: pref. in Data and AI,  4+ years in AI/ML engineering are preferred, with 2+ years specifically focused on agentic AI or GenAI applications.

Mentioning below skills are required in hands-on experience on projects in the last 3-4 yrs.

·         Python

·         Prompt Engineering

·         Hands-on experience with SOTA LLMs, Langraph/LangChain, Google ADK

·         Tag routing experience with MetaRouter / Segment / Tealium and Martech tools like Growthloop or Optimizely

·         Hands-on experience architecting, building and scaling complex Agentic and multi-agent solutions, including agent orchestration, inter-agent communication, conflict resolution, failure handling and production-grade Agentic AI engineering practices.

·         Proven experience identifying, evaluating and resolving conflicting information, reasoning or recommendations across agents, tools and data sources.

·         Hands-on proficiency designing, building and consuming MCP servers, including efficient tool/resource design, secure integration and scalable, sustainable implementation patterns.

·         Relevant demonstrable experience building agentic workflows with agents that reason, capture feedback, and self-learn to improve subsequent flows.

·         Agentic RAG/RAG/GraphRAG framework

·         Evaluate and optimize Agent output and performance, including reliability, observability, context management, failure/degradation handling and production readiness.

·         Ability to interact with business teams and convert business needs to AI/ML workflows - Must demonstrate end-to-end business context — not just technical implementation.

·         SQL/BigQuery/Google Cloud Platform, with hands-on experience designing and deploying AI/Agentic solutions on Google Cloud Platform strongly preferred.

Preferred skills:

·         Redis, Context Engineering; demonstrable experience with A2A (Agent2Agent) protocol and interoperable agent-to-agent communication patterns is a strong plus.

·         Preferred background in Telecom, with subject matter knowhow of customer touchpoint processes and CX workflows.