Senior AI Engineer
adp
Job Description
- Diagnose before building: map how the work is done today, find the constraint, and confirm the technology fits.
- Build natural-language querying over our structured and unstructured data, including structure extracted from invoices and contracts.
- Build semantic search spanning our products, delivered as a single entry point.
- Build the agentic platform: orchestration, the tool interface standard and registry, memory, budgets, retries, fallbacks, and human checkpoints.
- Close the loop on agent behavior: capture production feedback and apply the right technique — offline evaluation, preference data, bandits, or reinforcement learning — so agents improve and take on autonomous work.
- Build evaluation infrastructure: task datasets, failure taxonomies, regression suites wired into release, and LLM-as-judge calibrated against human agreement.
- Design guardrails: prompt injection defense, output filtering, access control, and audit trails.
- Own model cost: routing on quality, latency, and price.
- Own initiatives end to end, through production and iteration, including a clean handoff to the owning team.