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/GCP, with hands-on experience designing and deploying AI/Agentic solutions on GCP 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.