AI Software Engineer

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.

If you are needing any extra assistance or have any questions relating to a job you have applied for, please click the link below and find the agency for which you applied for additional information:

• Agency Contact