About the RoleWe are building a fleet of specialized AI services that improve high-value human workflows across the company. As a
Senior Software Engineer, Core AI, you will design, build, evaluate, and operate production-grade AI services and agents. You will own work end to end-from data and context design through tool use, application logic, evaluation, and production monitoring.
What You'll Do:- Build specialized AI services: design and implement task-specific services and agents, including data serialization, retrieval, memory where appropriate, tool integrations, and bounded multi-step reasoning.
- Define and evaluate quality: work with partners to make expected behavior explicit, write and maintain evals against representative examples, and use results to measure performance against expectations.
- Improve quality systematically: use evaluation findings, failure analysis, and production feedback to improve context and data, service logic, tools, and model behavior.
- Build for production: integrate tracing, observability, versioning, monitoring, reliability practices, and success metrics into the services you own.
- Run controlled experiments: compare models, data, and implementation approaches using repeatable benchmarks so improvements are attributable and reproducible.
- Partner on architecture: work with AI Architecture, AI Ops, and Platform teams to make services secure, reliable, cost-aware, and deployable at scale.
- Ship iteratively: move quickly from user problem to prototype to production, learning from real workflow outcomes.
What We're Looking For:- 5+ years of strong software engineering experience delivering production services or products, ideally at senior or staff level.
- Hands-on experience building AI/LLM-powered applications or agents with real users or operational use.
- Experience with evaluation methods for AI behavior: defining expected outcomes, building test sets or evals, tracking regressions, and acting on results.
- A data-first mindset: able to shape retrieval, context, and serialization to give a model the information needed for the task.
- Good judgment about tool use, autonomy, human review, failure handling, privacy, reliability, latency, and cost.
- A product-minded approach focused on solving specific workflow problems and measuring whether the solution works.
- Comfort learning tools and frameworks; experience with agent runtimes, model APIs, MCP, tracing, or evaluation tools is helpful.
The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate's starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate's skills and experience, market demands, and internal parity.
For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.
Pay Range
$113,400-$252,000 USD
