AI Platform & Data Engineer

Position Overview

Our collaborations have shaped some of the defining moments in public-sector service delivery. We’ve helped build products that connect Veterans to tailored services, help millions access affordable health care, and support important programs like Head Start. As we work with agencies to deliver critical services, we’re also changing how the government approaches technology.

Our culture, communications, and tools are built for remote work, enabling us to bring together top talent nationwide. At Ad Hoc, remote life empowers our teams to design work environments that fit their lives and foster flexibility and collaboration to achieve positive outcomes for our customers.

Ad Hoc values acceptance, accountability, and humility. We learn from our mistakes and continuously improve. Our small, inclusive teams collaborate closely with our partners to solve the right problems and deliver software that works. The Federal Civilian business unit supports federal, commercial, and nonprofit customers including NASA, the General Services Administration, Office of Personnel Management, the Library of Congress, Health & Human Services, and the FDIC.

Key Responsibilities

• Design, build, and operationalize a scalable AI/ML infrastructure to support multi-agent AI systems.
• Implement the Model Control Plane (MCP) for model lifecycle management and provide reusable AI services and data foundations.
• Research and integrate AI agent frameworks (e.g., LangChain) and design the MCP for model registry and lineage tracking.
• Develop shared foundational services such as a managed vector database for retrieval-augmented generation (RAG) and distributed caching, while integrating Human-in-the-Loop (HITL) workflows for safe agent operation.
• Utilize strong influential skills to propose and evaluate multiple approaches to technical and process challenges.
• Mentor team members and, when necessary, lead small or temporary team structures and projects.
• Present design documents, system diagrams, and related materials to clients, stakeholders, partners, and fellow engineers.
• Implement data engineering best practices and generate data architecture recommendations.
• Diagnose and resolve issues with owned systems, using incidents as opportunities for improvement and learning.
• Effectively communicate technical issues and developments with team members and clients.
• Participate in technical interviews with new candidates.

Required Qualifications

• Education: Bachelor’s degree (relevant experience may be substituted)
• Experience Required: 7+ years of experience in data engineering or related fields
• Demonstrated expert-level knowledge in at least one family of data ingestion systems, cloud database services, and visualization software.
• Expertise in key data concepts including database construction, big data processing, and data accuracy improvement.

Preferred Qualifications

• Strong experience as a cloud data engineer.
• Expertise in AI/ML workflows, model deployment, and observability (latency, throughput).
• Ability to design for data privacy and implement technical AI guardrails.
• Proficiency in Python (primary language), SQL, Spark/Databricks, Kubernetes/ECS, OpenAPI, and experience with vector databases and feature stores.