Ad Hoc LLC is a technology company that empowers organizations to deliver scalable, impactful digital services. They are seeking a Senior AI Platform & Data Engineer to design and implement scalable AI/ML infrastructure, manage model lifecycles, and enhance data engineering processes.
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. 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
Requirements:
- 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
- Strong experience with data engineer 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