Staff Software Engineer, Search Retrieval Platform
About The Position
Advanced Content Engineering (ACE) is seeking a Staff Software Engineer to build platform capabilities that let product teams, research teams, and AI agents access high-quality, customizable search without building it from scratch. The role focuses on understanding customer needs and translating them into reusable, self-service retrieval capabilities. The engineer will work with product, research engineering, and applied science partners across APIs, search services, agents, evaluation and grading, authentication, and security. The platform serves end customers, AI agents, and internal systems at enterprise scale. Staff Engineers define, build, deploy, and operate their work, shipping frequently and using AI-assisted development as the norm. The position also sets technical direction for retrieval, search services, and APIs; leads cross-team initiatives; and mentors other engineers. Success includes improving retrieval quality, reliability, or customizability, delivering capabilities adopted independently by client teams, establishing evaluation coverage and operational practices, and bringing research innovations into supported platform capabilities.
Requirements
- 8+ years of software engineering experience, with progression to staff-level scope, including ownership of a functional area and cross-functional leadership.
- A degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Experience building search, retrieval, or data-intensive platforms at scale, with strong distributed systems fundamentals and experience in a language such as Python, Java, or Go.
- Track record of translating customer needs into platform capabilities across product, engineering, and science.
- Experience designing APIs and services consumed by multiple teams, with attention to contracts, versioning, and developer experience.
- Operational rigor, including SLOs, observability, on-call ownership, and learning from incidents.
- Fluency with AI-assisted development tools.
Nice To Haves
- Production experience with search engines such as Vespa, OpenSearch, or Elasticsearch.
- Experience with hybrid (dense and sparse) retrieval, ranking, and embedding pipelines.
- Experience building tools or APIs for AI agents, including agentic retrieval patterns and protocols such as MCP.
- Search evaluation experience, including relevance metrics, LLM-as-judge, and online experimentation.
- Experience with multi-tenant authentication, authorization, and entitlements.
- Experience operationalizing ML models in production, including serving, promotion, and monitoring.
Responsibilities
- Translate customer and product needs into platform capabilities by working with product teams, client teams, and agent builders.
- Design retrieval APIs and search services for end users, AI agents, and internal systems, with consistent contracts, tunable filtering and ranking, predictable latency, and result payloads suited to agent context windows.
- Build customizable, pluggable components for chunking, enrichment, embedding, ranking, and custom models that teams can compose and tune through self-service APIs.
- Own content ingestion and indexing, including streaming pipelines, search engine configuration, and zero-downtime index changes.
- Partner with Research Engineering and Applied Science to move retrieval techniques from experiment to supported platform capability.
- Work with product and client teams to prioritize the roadmap, incorporate adoption feedback, and reduce time-to-value for new adopters.
- Build evaluation capabilities, including offline evaluation, search grading, LLM-as-judge scoring, and online experiments.
- Own retrieval security, including multi-tenant data isolation, query-time entitlement enforcement, and telemetry that protects user content.
- Own SLOs, observability, and on-call responsibilities for delivered systems; include tracing for agentic retrieval paths and drive improvements based on incident reviews.
- Set architectural direction and design patterns for retrieval, search services, and APIs.
- Lead cross-team initiatives, set priorities, and balance near-term product needs with the long-term platform.
- Mentor Senior and mid-level engineers and help the team use AI-assisted development effectively.
Benefits
- Flexible hybrid work environment for office-based roles.
- Work-from-anywhere arrangements for up to 8 weeks per year.
- Flexible vacation and paid time off, including sick and safe time and paid holidays.
- Two company-wide Mental Health Days off annually.
- Access to the Headspace app and Employee Assistance Program.
- Health, dental, vision, disability, and life insurance.
- 401(k) plan with company match.
- Parental leave and sabbatical leave.
- Tuition reimbursement.
- Employee incentive programs and an Employee Stock Purchase Plan.
- Flexible Spending and Health Savings Accounts.
- Fitness reimbursement.
- Commuter benefits.
- Adoption and surrogacy assistance.
- Two paid volunteer days off annually and opportunities for pro-bono consulting and ESG initiatives.
- Resources for mental, physical, and financial wellbeing.
- Optional hospital, accident and sickness insurance; optional life and AD&D insurance; and group legal and identity theft protection.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
