Forward Deployed Engineer-FDE AI Applications Dev

The Forward Deployed Engineer (FDE) 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 be able to work at the intersection of modern software engineering, cloud-native architecture, AI-enabled development, automation, security, and agency mission delivery. Rather than prescribing a specific cloud platform, LLM provider, or toolchain, the role should emphasize the ability to evaluate technologies based on business need, security posture, data sensitivity, interoperability, cost, operational maturity, and long-term sustainability.

The ideal candidate should help DIR and agencies understand what is possible with modern technology, translate emerging capabilities into practical delivery patterns, and coach internal teams on how to adopt those capabilities responsibly. This includes helping teams turn ambiguous problems into practical, AI-enabled workflows, while exploring AI, automation, APIs, integration patterns, DevSecOps, and reusable components. Focus 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. The role should be aspirational in terms of skill level and innovation, but not overly prescriptive in terms of specific products, platforms, or implementation methods.

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., * Deliver high-quality application, Application Programming Interface (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.
• Comfort working across cloud environments and internal enterprise systems.

Must have Linkedin and 14+ years of exp.

• Active Texas DL & LinkedIn ID Must for submission, Strong proficiency in: TypeScript/JavaScript, Python, or C#; Modern UI frameworks (React, Angular, Web Components).

8

Required

Experience with integrating APIs (LLMs, internal services, data platforms).

8

Required

Experience with CI/CD platforms using GitHub Actions, Azure DevOps, or equivalent including building and deploying applications.

8

Required

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

Required

Extend tools like Salesforce, Appian, ServiceNow, etc. Demonstrated success delivering systems end-to-end from design deploy.

8

Required

Understanding of security frameworks (NIST, Zero Trust, TX-RAMP expectations).

8

Required

Excellent communication and cross-functional collaboration skills.

8

Required

Ability to decide when NOT to use low-code.

8

Required

Ability to identify high-value use cases and ability to observe workflows.

8

Required

Bachelor s degree in Computer Science, Engineering, or related field OR Equivalent experience (10+ years) in hands-on modern engineering roles.

8

Preferred

Experience in state government, regulated environments, or multi-agency integration projects.

8

Preferred

Prior FDE or technical field engineering experience at a software platform company.

8

Preferred

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...cont. next line...

8

Preferred

prompt management, human-in-the-loop review, and responsible AI controls.Experience with shared technical services or modernization programs (e.g., TSS/MSI) .

8

Preferred

Experience producing reusable components, design systems, developer tooling.

8

Preferred

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.

8

Preferred

CISSP, CCSP, or CISM

8

Preferred

Kubernetes certifications (CKA/CKAD)

8

Preferred

TOGAF or architecture certifications

8

Preferred

Scrum Master or SAFe Agile certs

6

Preferred

TX-RAMP knowledge or auditor training

1

Preferred

Cloud architecture, DevOps, AI, security, or Kubernetes certifications from one or more major providers, such as Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, ISACA, or equivalent.