Agentic AI Platform Engineer (with MLOps Expertise)

Role Summary The Agentic AI Platform Engineer builds scalable, reusable, production-grade agentic infrastructure components. This role focuses on creating standardized Agentic AI constructs — including MCP servers, connectors, agent orchestration templates, memory frameworks, evaluation pipelines, and deployment patterns — with enterprise-grade MLOps discipline. Key Responsibilities Agentic Platform Engineering (Build reusable Agentic components): MCP (Model Context Protocol) servers, MCP registries, MCP gateways Data Connectors (SQL, Databricks, NetDocs, APIs) Tool orchestration frameworks Memory & context management services (Short term, long term memory) Create standardized agent templates for common agent patterns LLM & Agent Orchestration (Design & deploy agents: Multi-agent architectures and design patterns Design Tool invocation frameworks, memory management framework Define and implement guardrails and policy enforcement at runtime. MLOps & AI Engineering Implement CI/CD for AI agents. Manage model lifecycle using: MLflow, Model registry, Version control for prompts and agents Establish: Evaluation pipelines, Observability, Latency monitoring, Hallucination detection, Security testing