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