Job Posting Title
AI Software Engineer
Agency
090 OFFICE OF MANAGEMENT AND ENTERPRISE SERV
Supervisory Organization
IS-Data
Job Posting End Date
Refer to the date listed at the top of this posting, if available. Continuous if date is blank.
Note: Applications will be accepted until 11:59 PM on the day prior to the posting end date above.
Estimated Appointment End Date (Continuous if Blank)
Full/Part-Time
Full time
Job Type
Regular
Compensation
Job Description
As an AI Software Engineer with OMES you will enjoy:
- Generous leave including 15 days of vacation, 15 days of sick leave and 11 paid holidays annually.
- A comprehensive Benefit Package with a generous benefit allowance to offset the cost of insurance premiums for employees and their eligible dependents.
Job Details
- Full-time 40-hour work weeks
- Support the Information Services Division
- Salary is based on education and experience
- This is an on-site position located in Oklahoma City, OK
Position Summary
The AI Software Engineer owns the agency’s custom AI development on Microsoft Foundry (formerly Azure AI Foundry). This is a hands-on engineering role with a clear mandate: turn AI delivery from a series of one-off projects into a repeatable, industrialized pattern that lets the organization deliver more AI solutions, faster, at a lower cost per solution.
The role inherits AI products already running in production. The engineer will take full ownership of them – stabilizing, hardening and supporting the code – while extracting what works into a shared core capability that every future AI solution is built on. Success means each new use case is a configuration of proven components, not a new build from scratch.
Key Responsibilities
Reusable AI Platform & Delivery Pattern (Economy of Scale)
- Design and maintain a reference architecture for AI solutions on Microsoft Foundry, including Foundry Agent Service, Foundry Models, Azure OpenAI and Azure AI Search / Foundry IQ grounding.
- Build reusable starter templates, shared SDK/libraries and infrastructure-as-code modules so new use cases can be stood up in days rather than months.
- Standardize common building blocks: prompt and agent configuration, retrieval-augmented generation (RAG) pipelines, tool/API connectors, model routing, conversation state and error handling.
- Define a repeatable intake-to-production lifecycle (discovery, prototype, evaluation, security review, deployment, support handoff) and continually refine it based on lessons learned.
- Identify duplicated logic across products and refactor it into the shared core; retire one-off code wherever possible.
- Track and optimize unit economics – token consumption, model selection, compute and hosting cost – and design for cost efficiency at scale.
Inherited Product Ownership & Code Hardening
- Assume technical ownership of existing production AI products; perform an early assessment of architecture, code quality, security, dependencies and technical debt.
- Develop and execute a prioritized hardening plan: automated unit, integration and regression tests; static and dependency scanning; secrets management; resiliency and retry patterns; rate-limit and quota handling.
- Migrate inherited products onto the shared core capability and standard pipelines as the pattern matures.
- Implement automated AI evaluation (groundedness, relevance, accuracy, safety) as release gates, and maintain regression test sets for each product.
- Deliver enhancements and new features against a prioritized backlog in partnership with product owners and business stakeholders.
Production Operations & Support
- Provide ongoing support for AI products, including participation in an on-call rotation and incident response for production issues.
- Instrument products with telemetry, tracing and dashboards (Azure Monitor, Application Insights, Foundry observability) covering latency, error rates, cost and model quality.
- Define service level objectives with stakeholders and monitor model and prompt drift, degradation and anomalous usage.
- Perform root cause analysis, write post-incident reviews and drive corrective actions back into the shared platform.
- Manage model version lifecycles, deprecations and upgrades with minimal disruption to users.
Security, Governance & Responsible AI
- Apply secure-by-design practices: managed identities, least-privilege RBAC, private networking, key and secrets management, and data protection appropriate for government data.
- Implement content safety, prompt-injection defenses, input/output filtering and human-in-the-loop controls where required.
- Support the agency’s AI governance framework, documentation and audit requirements, including model cards, data lineage, risk assessments and records retention.
- Ensure solutions meet applicable state policy, privacy, accessibility (WCAG / Section 508) and security standards.
Collaboration, Enablement & Documentation
- Work within an agile delivery model alongside DevSecOps, SRE, Observability, infrastructure, security and data teams.
- Produce clear architecture documentation, runbooks and developer guides so the pattern can be adopted by other engineers and vendors.
- Coach developers and contractors on the standard pattern; perform code reviews and enforce engineering standards.
- Translate business problems into technical approaches and communicate trade-offs to non-technical stakeholders and leadership.
Physical Demands and Work Environment
While performing the duties of this job, this position works in an office setting with a computer for a large percentage of the workday. The noise level in the work environment is usually moderate. Occasional travel may be required.
This position participates in an on-call rotation for production AI services, including occasional after-hours support.
Minimum Qualifications
Requirements include a Bachelor’s degree in Computer Science, Software Engineering or a related field and 6+ years of professional software development experience building and supporting production applications, plus 2+ years developing generative AI or LLM-based solutions in production, including RAG and/or agent-based architectures, or equivalent combination of education and experience.
Preference will be given to candidates who possess
- Microsoft Certified: Azure AI App and Agent Developer Associate (AI-103) or predecessor Azure AI Engineer Associate (AI-102); Azure Developer or DevOps Engineer certifications.
- Experience with Foundry Agent Service, Semantic Kernel / Microsoft Agent Framework, multi-agent orchestration or Model Context Protocol (MCP) tooling.
- Experience with AI evaluation frameworks, LLMOps practices and prompt/version management.
- Background in public sector, regulated industries or environments with strict security and compliance requirements.
- Experience with FinOps or IT cost management for cloud and AI workloads.
- Familiarity with Power Platform, Copilot Studio or Microsoft 365 integration.
About OMES
The Office of Management and Enterprise Services provides excellent service, expert guidance and continuous improvement in support of our partners’ goals. We are a highly qualified workforce committed to serve those who serve Oklahomans and make government run in the most efficient, innovative manner possible.
OMES is an Equal Opportunity Employer. Reasonable accommodation to individuals with disabilities may be provided upon request.
Equal Opportunity Employment
The State of Oklahoma is an equal opportunity employer and does not discriminate on the basis of genetic information, race, religion, color, sex, age, national origin, or disability.
Current active State of Oklahoma employees must apply for open positions internally through the Workday Jobs Hub.
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