Artificial Intelligence/Machine Learning Engineer
About The Position
The Artificial Intelligence/Machine Learning Engineer will support the Texas Department of Information Resources on the Forward Deployed Engineer (FDE) initiative. This role works directly with DIR and partner agencies to rapidly design, build, deploy, and iterate modern digital solutions, often working onsite or embedded with mission teams. The position combines hands-on engineering, rapid prototyping, and production deployment to accelerate modernization and reduce reliance on legacy integrator models. The engineer will bridge product, security, business, and cloud engineering teams, evaluating AI/LLM capabilities based on business need, security posture, data classification, interoperability, and total cost of ownership rather than defaulting to a single vendor or platform. The role also includes delivering knowledge transfer sessions and coaching internal agency staff to build long-term technical capability. This position requires the ability to translate ambiguous problems into practical, AI-enabled workflows while preserving architectural flexibility.
Requirements
- 8 years of hands-on software engineering experience.
- 8 years of expertise in modern cloud platforms.
- 8 years of strong proficiency in TypeScript/JavaScript, Python, or C#, and modern UI frameworks such as React, Angular, or Web Components.
- 8 years of experience integrating APIs, including LLMs, internal services, and data platforms.
- 8 years of experience with CI/CD platforms such as GitHub Actions or Azure DevOps, including building and deploying applications.
- 8 years of experience with infrastructure as code and environment automation tools such as Terraform or ARM/Bicep, including experience working directly with customers or frontline operational teams to build and improve solutions.
- 8 years of experience extending tools such as Salesforce, Appian, or ServiceNow, with demonstrated success delivering systems end-to-end from design through deployment.
- 8 years of experience with security frameworks such as NIST, Zero Trust, and TX-RAMP expectations.
- 8 years of experience with cross-functional collaboration and communication in a technical environment.
- Demonstrated ability to determine when not to use low-code solutions.
- Demonstrated ability to identify high-value use cases and observe workflows.
- Bachelor's degree in Computer Science, Engineering, or a related field, or 10 years of equivalent hands-on experience in modern engineering roles.
Nice To Haves
- Experience in state government, regulated environments, or multi-agency integration projects.
- Prior Forward Deployed Engineer (FDE) or technical field engineering experience at a software platform company.
- Experience designing, evaluating, or implementing AI-enabled workflows using commercial, open-source, or government-approved LLM platforms, including retrieval-augmented generation, agentic workflows, model evaluation, prompt management, human-in-the-loop review, and responsible AI controls.
- Experience with shared technical services or modernization programs, such as TSS/MSI.
- Experience producing reusable components, design systems, and developer tooling.
- Ability to compare AI/LLM options using objective criteria such as data sensitivity, hosting model, latency, cost, accuracy, explainability, auditability, security controls, integration complexity, and operational sustainability.
- CISSP, CCSP, or CISM certification.
- Kubernetes certification (CKA/CKAD).
- TOGAF or other architecture certification.
- Scrum Master or SAFe Agile certification.
- TX-RAMP knowledge or auditor training.
- Cloud architecture, DevOps, AI, security, or Kubernetes certification from a major provider such as Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, or ISACA.
Responsibilities
- Deliver high-quality application, API, Model Context Protocol (MCP), and automation components using cloud-native architectures.
- Develop rapid prototypes, pilots, and production systems using modern engineering patterns.
- Integrate systems across agencies using secure, scalable, human-in-the-loop workflows.
- Implement DevSecOps automation, including CI/CD, infrastructure as code, and container orchestration.
- Collaborate directly with agency stakeholders to gather requirements and convert them into working software.
- Deploy AI-enabled development workflows and LLM-assisted capabilities.
- Troubleshoot complex production issues and lead root-cause analysis.
- Mentor agency developers to mature internal capability and reduce vendor reliance.
- Provide documentation, architectural guidance, and knowledge transfer to agency staff.
- Build AI-powered tools using existing systems and create new applications to move from experimentation to real-world impact.
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What This Job Offers
Job Type
Full-time
