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Today

Senior AI Engineer – Agentic AI Platform

Hudson Manpower Cincinnati, OH

Cincinnati, OH

Today

$55 - $60/hr Full time Backend Developer Agentic Ai Ai Agent

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Job Description

Hudson Manpower is hiring a Senior AI Engineer to help design and deliver an enterprise-scale agentic AI platform. This onsite role in Cincinnati, OH focuses on building the capabilities needed to create, deploy, monitor, govern, and operate autonomous AI agents across business domains, with a cloud-native approach on Azure.

The work spans multi-agent orchestration patterns, AI platform architecture, governance and FinOps controls, memory and RAG, observability and evaluation, and responsible AI guardrails for sensitive, regulated enterprise contexts.

What you will do

Design and develop multi-agent AI systems for enterprise use cases.
Build autonomous and semi-autonomous AI workflows.
Implement agent orchestration and workflow patterns including Supervisor-Worker, Sequential, ReAct, Planner-Executor, and Writer-Critic, including orchestration and choreography approaches.
Develop scalable frameworks for agent communication and execution.
Create closed-loop workflows that include validation, retry, evaluation, and feedback mechanisms.
Build reusable AI platform capabilities that multiple business teams can use.
Design enterprise AI governance and operational controls for agent operations.
Develop API-driven AI services with operational and security features such as rate limiting, quota management, authentication, authorization, audit logging, multi-tenant usage tracking, and cost attribution.
Establish agent onboarding and lifecycle management capabilities.
Implement agent communication using direct calls, event-driven architectures, message queues, and publish-subscribe patterns.
Work with Kafka and Azure event tooling including Azure Service Bus and Azure Durable Functions to support event-driven workflows.
Design short-term and long-term AI memory architectures, including vector databases, semantic caching, conversation memory, and agent state persistence.
Build knowledge orchestration frameworks for agent collaboration, including support for graph databases and enterprise knowledge models.
Support ontology-driven AI applications and implement knowledge graphs for relationship-based reasoning.
Integrate structured, unstructured, and graph-based knowledge sources.
Implement AI consumption governance across business domains, including token usage tracking and operational cost monitoring.
Develop chargeback/showback mechanisms and support AI FinOps reporting and capacity planning.
Design observability for AI applications, including monitoring agent execution, tool usage, latency, hallucinations, failure rates, and model quality.
Build dashboards and operational metrics for AI workloads.
Implement guardrails and safety controls including prompt protection, data masking, PII protection, and human-in-the-loop validation.
Ensure compliance with enterprise security and governance requirements, including secure agentic AI systems for sensitive business data.
Develop agent and tool evaluation frameworks, including response quality measurement and hallucination detection, and implement closed-loop evaluation mechanisms.
Apply context engineering, prompt engineering, retrieval optimization, agent tuning, and AI benchmarking.

Minimum requirements

8–10 years of software engineering or platform engineering experience.
3+ years of hands-on AI/ML or Generative AI experience.
Production experience building enterprise-scale AI applications.
Strong experience designing AI architectures and platforms (not only individual AI applications).
Hands-on experience with Agentic AI / AI Agents.
Strong experience with Azure, including Azure AI Foundry and Azure OpenAI.
Strong experience with LangChain and/or LangGraph.
Strong Python development experience.
Experience with multi-agent orchestration and agentic workflow patterns.
Experience with RAG, vector databases, AI memory, and agent state management.
Experience with REST APIs and API gateways, preferably Azure API Management (APIM).
Experience with event-driven architectures and messaging systems.
Experience with AI monitoring, observability, governance, and cost/token usage tracking.
Experience with enterprise data/storage technologies such as Cosmos DB, PostgreSQL, MongoDB, or vector databases.
Experience with SQL.
Experience designing scalable, secure, and governed AI platforms.

Useful technologies

Azure, Azure AI Foundry, Azure OpenAI, LangChain, LangGraph, Python
Vector databases, RAG, REST APIs, API gateways, Azure API Management (APIM)
Kafka, Azure Service Bus, Azure Durable Functions
Message queues, publish-subscribe patterns, event-driven architectures
Cosmos DB, PostgreSQL, MongoDB, SQL

Desirable skills

Semantic Kernel
Model Context Protocol (MCP)
C# / .NET
Azure Event Grid
Graph databases such as Neo4j, Stardog, Amazon Neptune, or other graph databases
Enterprise knowledge graphs and ontology-driven AI solutions
AI FinOps and chargeback/showback, responsible AI frameworks, and AI evaluation and benchmarking
AWS or GCP experience
Experience in healthcare, financial services, insurance, or other regulated industries

Location: Cincinnati, OH (onsite). Compensation: USD 55–60 per hour.

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