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Today

AI Engineer III

Cerium Networks Inc Beaverton, OR

Beaverton, OR

Today

$110k - $150k/yr Full time Backend Developer APIs Artificial Intelligence

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Job Description

Build secure generative AI and full-stack features for real client outcomes with Cerium Networks’ Data & AI implementation services team. This hybrid role is based in Beaverton, OR (1-day onsite) and supports delivery of custom solutions on Cerium’s AI Agent Platform hosted on Azure, combining software engineering, AI model/service integration, and deployment.

What you’ll deliver

Own technical delivery end-to-end for client engagements, from architecture and estimation through implementation, testing, deployment, documentation, and handoff of AI solutions (agents, automation workflows, and Gen AI models) using established best practices.
Lead technical conversations with customers to gather requirements and clarify the capabilities of the solutions and services you will build.
Deploy software to the Agent Platform on Azure, using CI/CD pipelines to enable automated builds and releases when needed.
Integrate custom AI solutions with third-party applications, modern data architecture, and cloud services.
Provide technical consulting throughout the software development lifecycle, including solution proposals, feedback incorporation, and administrative handoffs after implementation.

Leadership across engineering, AI, and delivery

Provide technical leadership and mentoring for junior engineers through architecture and code reviews and implementation guidance.
Apply best practices across AI/ML, DevOps, security, and cloud architecture.
Support pre-sales and sales teams by helping design proposed solutions and provide estimated levels of effort when required.

Core requirements

Bachelor’s degree in software engineering, applied artificial intelligence, or a related field, or equivalent experience.
7+ years of full-stack development experience with Python and Azure.
Proven experience deploying AI agents or Generative AI solutions with Python, FastAPI, LangChain / LangGraph, and Azure.
Client consulting experience, including the ability to explain complex technical concepts clearly to non-technical audiences.
Ability to manage multiple tasks, projects, and clients simultaneously, with strong organization and documentation.
Customer service skills and experience.
Willingness to travel 10% to 20% of the time based on client needs.

Technologies you’ll work with

Python, FastAPI, LangChain / LangGraph
Microsoft Azure, Azure DevOps, Azure Container Apps
Cosmos DB, Azure Container Registry
Snyk, ISO 27001

Benefits

Medical, dental and vision insurance
Basic term life and AD&D insurance (fully paid by the company)
Paid time off: 15 days PTO and 9 paid holidays annually
401(k) plan with employer matching contribution of 4%
Wellness program with up to $500 in cash awards
Employee Assistance Program

Preferred qualifications

Experience with Azure Container Apps, Cosmos DB, and Azure Container Registry
3+ years in consulting/professional services
DevSecOps skills and experience with Snyk or other vulnerability scanning tools
Experience ensuring software meets ISO 27001 compliance standards
Certifications across AI and DevOps solutions, including: AI-103, AI-200, AZ-204 / AZ-400, and DP-420

Compensation: Pay Range $110,000 - $150,000 per year. Actual compensation may vary and may be above or below the range based on location, experience, and performance, among other factors.

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1mo ago

Senior AI Engineer – Agentic AI Platform

Hudson Manpower Cincinnati, OH

Cincinnati, OH

1mo ago Closed

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

This position is no longer accepting applications (closed Sep 28, 2026).

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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Azure Cosmos Db Data Jobs

AI Engineer III

Senior AI Engineer – Agentic AI Platform

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