Description

Skill Requirements-

• Build production-grade AI Agents using LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, and LlamaIndex.
• Design Agentic RAG solutions over telecom documentation, alarms, KPIs, topology, inventory, and operational runbooks.
• Implement ingestion, chunking, embeddings, vector retrieval, reranking, grounding, and citation generation.
• Develop AI microservices using Python, FastAPI, REST APIs, AsyncIO, and containerized architectures.
• Create MCP Servers and MCP Clients exposing approved telecom tools, repositories, databases, and APIs.
• Integrate LLMs through Vertex AI and enterprise model gateways with prompt caching and model routing.
• Develop multi-step agent workflows with tool calling, contextual memory, state management, and human approvals.
• Apply 5G Core, IMS, EPC, OSS/BSS, assurance, and operational domain expertise to agent design.
• Design structured tool contracts and agent interfaces for reusable telecom capabilities.
• Build evaluation pipelines covering grounding, telecom correctness, hallucination detection, latency, and safety.
• Implement observability for prompts, retrieval quality, tool invocations, token usage, and business outcomes.
• Integrate agents with PostgreSQL, vector databases, Kafka/PubSub, enterprise APIs, and telemetry platforms.
• Implement Responsible AI controls, access controls, auditability, approval workflows, and security guardrails.
• Deploy solutions on GKE/Cloud Run using Docker, GitLab CI/CD, automated testing, and release pipelines.
• Own production rollout, incident analysis, operational readiness, regression testing, and service evolution

Key Skills

Education

Bachelor's degree