Job description

About OPEN Data Jobs OPEN Data Jobs (ODJ) is built to craft data careers. We connect high-potential data, AI, and software professionals with meaningful work on the cutting edge of the federal sector, and our aim reaches beyond any single opening: to help you understand your strengths, find the right role, and grow throughout your career. ODJ is organized around Roles and Openings. A Role is a durable career type, such as Data Engineer or AI Engineer: it describes the work, the skills that count, and where the path can lead. An Opening is a specific position hiring right now, with a level, a location, and an application. Roles help you see where you fit; from there, there is more than one way to move. Today, you can apply to any Opening that fits you through our secure application system. You can also register for a Role to express interest in that broader category of work. A Role registration is not an application to every future Opening. The work AI Engineers build and operate systems that turn data, documents, models, and AI services into useful applications and workflows. The work runs from understanding the problem and preparing inputs through model or service selection, system design, evaluation, deployment, monitoring, incident response, and continuous improvement. This is systems engineering around AI behavior. AI Engineers connect data pipelines, models, APIs, user experiences, business rules, and human-review paths, then test the complete system under conditions that reflect how people will use it. They make limitations visible and match security, traceability, and oversight to the consequences of the work. What you'll build • Document and content pipelines that apply OCR, parse layouts, extract and validate information, preserve provenance, and make authoritative content usable downstream. • Predictive, classification, recommendation, natural language, computer vision, or decision-support services that combine custom models, pretrained models, externally provided AI services, and deterministic software. • Search and knowledge applications that use retrieval, retrieval-augmented generation (RAG), controlled source access, and traceable references. • Workflow and agent-based systems with scoped tools, permission boundaries, approval paths, exception handling, and audit trails where agentic patterns fit the problem. • Evaluation and operations capabilities that version, test, release, trace, monitor, diagnose, and roll back models, prompts, configurations, retrieval indexes, and supporting software. Who you are You see the model as one part of a larger system. You can move between user needs, data, software, model behavior, and production operations without losing sight of the outcome, and you choose the simplest approach that meets the need. You test assumptions against evidence, communicate tradeoffs clearly, and work comfortably with domain experts, users, data engineers, data scientists, Machine Learning Engineers, security specialists, governance teams, and operations teams. You know when to build, when to integrate, when to escalate, and when AI is not the right answer. What you bring • A working foundation in software engineering, including programming, APIs, testing, version control, and the design of services or applications. • Practical experience with structured or unstructured data, including preparation, validation, metadata, access controls, quality, and traceability. • Applied understanding of AI and machine learning, including model or service selection, evaluation design, error analysis, and clear communication of limitations. • Experience contributing to production reliability through deployment discipline, observability, performance and cost management, security, incident response, or related operational practices. • The judgment to match evaluation, documentation, safeguards, and human oversight to the context and consequences of the system. What openings may require An opening may emphasize document intelligence, conventional ML, generative AI, RAG, agents, computer vision, AI platforms, machine learning operations (MLOps), generative AI operations, evaluation, security, governance, or a particular mission domain. Specific openings may name programming languages, cloud environments, model providers, ML frameworks, document-processing tools, search or vector platforms, workflow and agent frameworks, data stores, container and deployment platforms, observability systems, or regulated-development practices. OPEN Data Jobs will identify the required and preferred capabilities with each opening. Compensation and benefits Compensation, benefits, work location, and employment terms are set for each specific opening and will be stated with that opening. Register for AI Engineer Role Click Apply below to register for AI Engineer Role.

Requirements

Must-haves

A working foundation in software engineering, including programming, APIs, testing, version control, and the design of services or applications.
Practical experience with structured or unstructured data, including preparation, validation, metadata, access controls, quality, and traceability.
Applied understanding of AI and machine learning, including model or service selection, evaluation design, error analysis, and clear communication of limitations.
Experience contributing to production reliability through deployment discipline, observability, performance and cost management, security, incident response, or related operational practices.
The judgment to match evaluation, documentation, safeguards, and human oversight to the context and consequences of the system.
What openings may require

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningml

Platform: workable
Effort: medium

Benefits

Benefits detected in the listing.

Vision