AI/ML Engineer

Hands-on software engineering experience.
Expertise in modern cloud platforms.
Strong proficiency in: TypeScript/JavaScript, Python, or C#; Modern UI frameworks (React, Angular, Web Components).
Experience with integrating APIs (LLMs, internal services, data platforms).
Experience with CI/CD platforms using GitHub Actions, Azure DevOps, or equivalent including building and deploying applications.
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.
Extend tools like Salesforce, Appian, ServiceNow, etc. Demonstrated success delivering systems end-to-end from design → 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 ability to observe workflows.

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...cont. next line...
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, 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
Kubernetes certifications (CKA/CKAD)
TOGAF or architecture certifications
Scrum Master or SAFe Agile certs
TX-RAMP knowledge or auditor training
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.