Artificial Intelligence / Machine Learning Consultant for Texas DIR, Austin, Tx

Location: North Austin, Texas 78758 | Duration: Ongoing, possibly four years | Contract Type: W2 with benefits | Visa requirements: US Citizen, Green Card Holder, EAD (no H1B) | Telework Policy: Hybrid (client site and telework)

About the Role

The Forward Deployed Engineer (FDE) 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 FDE combines hands-on engineering, problem solving, rapid prototyping, and production deployment to accelerate modernization and reduce dependency on legacy integrator models. The role bridges gaps between product teams, security, business units, and cloud engineering.

The FDE applies platform-agnostic engineering practices and evaluates AI/LLM capabilities based on business need, security requirements, data classification, interoperability, sustainability, and total cost of ownership rather than defaulting to a single cloud, model, or vendor ecosystem. The role provides FDE methodology and best practices to DIR staff for knowledge transfer and skill growth, supporting IT and other AI initiatives at DIR.

This role is intended to bring advanced, forward-looking technical capability to DIR and partner agencies while remaining flexible, platform-agnostic, and outcomes-focused. The consultant should work at the intersection of modern software engineering, cloud-native architecture, AI-enabled development, automation, security, and agency mission delivery. The ideal candidate helps DIR and agencies understand what is possible with modern technology, translates emerging capabilities into practical delivery patterns, and coaches internal teams on responsible adoption.

The role focuses on rapid prototyping and delivering value without assuming any single vendor or solution is always the right fit. The goal is to raise technical fluency, accelerate modernization, and build internal capability while preserving architectural flexibility.

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 (CI/CD, IaC, container orchestration, cloud pipelines).
• 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, maturing internal capability and reducing vendor reliance.
• Provide documentation, architectural guidance, and knowledge transfer.
• Rapidly build AI-powered tools using existing systems and create new applications where needed to move from experimentation to real impact.
• Work comfortably across cloud environments and internal enterprise systems.

Deliverables

• Production-ready code, pipelines, infrastructure templates, and documentation.
• Architecture diagrams, operational runbooks, and security compliance mappings.
• AI-assisted development workflows and accelerators.
• Knowledge transfer sessions and training for agency development staff.

Requirements

• 8 years of hands-on software engineering experience.
• 8 years of expertise in modern cloud platforms.
• Strong proficiency in: TypeScript/JavaScript, Python, or C#; modern UI frameworks (React, Angular, Web Components).
• 8 years of experience integrating APIs (LLMs, internal services, data platforms).
• 8 years of experience with CI/CD platforms using GitHub Actions, Azure DevOps, or equivalent, including building and deploying applications.
• 8 years of experience with infrastructure as code and automating environments (e.g., Terraform, ARM/Bicep, or similar tools).
• Experience working directly with customers or frontline operational teams to build and improve solutions.
• 8 years of experience extending tools like Salesforce, Appian, ServiceNow, etc.
• Demonstrated success delivering systems end-to-end from design to deploy.
• Understanding of security frameworks (NIST, Zero Trust, TX-RAMP expectations).
• Excellent communication and cross-functional collaboration skills.
• Ability to decide when NOT to use low-code.
• Ability to identify high-value use cases and observe workflows.
• Bachelor’s degree in Computer Science, Engineering, or related field OR equivalent experience (10+ years) in hands-on modern engineering roles.

Preferred Qualifications

• Experience in state government, regulated environments, or multi-agency integration projects.
• Prior 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 patterns such as 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 (e.g., TSS/MSI).
• Experience producing reusable components, design systems, or 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 certifications (CKA/CKAD).
• TOGAF or architecture certifications.
• Scrum Master or SAFe Agile certifications.
• TX-RAMP knowledge or auditor training.
• Cloud architecture, DevOps, AI, security, or Kubernetes certifications from major providers (e.g., Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, ISACA).