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

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