Senior Backend Engineer II, Data & Agentic Context Platforms

Responsibilities

• Design, build, and operate scalable backend services and APIs that ingest, transform, retrieve, and serve context to agents and product applications.
• Own batch and real-time data flows, including event ingestion, transformation, indexing, storage, and low-latency serving.
• Develop reusable agent-context capabilities, including connectors, context assembly, memory and state interfaces, metadata and provenance, authorization-aware retrieval, and evaluation signals.
• Define data models, schemas, and contracts; implement validation, lineage, freshness checks, and observability.
• Select storage and retrieval patterns across operational databases, data warehouses and lakes, search systems, caches, and graph or vector technologies.
• Establish SLIs and SLOs, monitor latency and correctness, plan capacity, manage costs, and design graceful failure and recovery paths.
• Translate ambiguous context needs into durable platform abstractions and lead technical designs through implementation, rollout, measurement, and adoption.
• Improve engineering velocity through SDKs, tools, documentation, deployment patterns, and paved paths.
• Mentor engineers and raise standards for backend architecture, data quality, operational excellence, and responsible use of context.

Requirements

• 8+ years of professional software engineering experience, including ownership of production backend or distributed systems at meaningful scale.
• Strong programming skills in at least one modern language such as Go, Python, Java, or Rust, plus proficiency in SQL and data modeling.
• Experience designing and operating APIs, asynchronous workflows, and data-intensive systems with demanding reliability, scalability, latency, and data-quality requirements.
• Experience with modern data infrastructure, including streaming or messaging systems, batch processing, operational databases, and cloud-based data platforms.
• Technical judgment regarding data consistency, schema evolution, privacy and access control, failure handling, performance, and cost.
• Experience with AWS, infrastructure-as-code tools such as Terraform or CloudFormation, CI/CD, and modern software delivery practices.
• Ability to lead ambiguous technical problems from architecture through adoption and improve systems based on evidence.
• Strong communication, collaboration, technical presentation, cross-functional alignment, and mentoring skills.
• Bachelor’s or advanced degree in Computer Science, Engineering, Data Science, Mathematics, or a related field, or equivalent practical experience.

Nice to Have

• Experience building production agentic or LLM-powered platforms, including context assembly, memory, retrieval, or evaluation systems.
• Experience with vector databases, graph technologies, search platforms, or hybrid retrieval approaches.
• Experience developing internal platforms, SDKs, or paved paths adopted by multiple engineering teams.
• Familiarity with authorization-aware retrieval and governance of sensitive data, including provenance, lineage, freshness, and privacy.

Compensation and Benefits

• Base salary range: $190,409–$224,011 USD.
• Equity, 401(k) match up to 4%, medical, dental and vision coverage, pet benefits, education reimbursement, employee resource groups, paid time off, paid holidays, year-end break, and parental leave.