[Hiring] Senior AI Platform & Data Engineer @Ad Hoc

Role Description

Senior AI Platform & Data Engineer serves as an emerging individual contributor within a team, expanding your leadership, guidance and mentoring skills. With the support and guidance of leadership, you will be responsible for supporting the goal of meeting scope, schedule and delivery requirements. You will interact with stakeholders and utilize influential skills to drive improvements in data engineering processes and practices. Primary expectations of a Senior AI Platform & Data Engineer include:

• 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. Provide reusable AI services and data foundations.
• Researching and integrating AI agent frameworks (e.g., LangChain). Designing the MCP for model registry and lineage tracking.
• Developing shared foundational services like a managed vector database (for RAG) and distributed caching. Integrating Human-in-the-Loop (HITL) workflows for safe agent operation.
• Builds data infrastructure, pipelines, systems, and tools with a little feedback and guidance from their team.
• Intermediate understanding of data management and transformation of raw data into interpretable information.
• Ability to create accurate and accessible datasets for Data Analysts and Scientists to interpret and use.
• Own maintenance of data architectures and systems.
• Practices technical and communications skills to improve context knowledge and mentor junior data engineers.
• Presents on and writes about their work to both internal and external parties.
• Participates in planning sessions, building an understanding of data architectures and infrastructure.
• Supports recruiting efforts by evaluating homework assignments and potentially assisting with interviews.

Qualifications

• Bachelor’s degree and 7+ years of experience.
• Relevant years of experience may be substituted for education.
• Proficient with at least one family of data ingestion systems, cloud database services, and visualization software.
• Background in key data concepts including constructing databases, processing big data, improving data accuracy, etc.

Requirements

• Strong experience with data engineering in the cloud.
• Expertise in AI/ML workflows, model deployment, and observability (latency, throughput).
• Ability to design for data privacy and implement technical AI guardrails.
• Python (primary language), SQL, Spark/Databricks (for large-scale data processing), Kubernetes/ECS, OpenAPI (for API documentation), experience with vector databases and feature stores.

Benefits

• Company-subsidized health, dental, and vision insurance.
• Flexible PTO.
• 401K with employer match.
• Paid parental leave after one year of service.
• Employee Assistance Program.