Staff Software Engineer — Search Platform, API & Infrastructure

About the role

The Advanced Content Engineering (ACE) team is seeking a Staff Software Engineer to lead the design and delivery of the search platform's control-plane API and cloud infrastructure. The platform's core promise is self-service: internal client teams must be able to create a search system, configure an ingestion topology, promote a new index to production, and monitor system health — entirely through APIs — without requiring direct involvement from the platform team.

Responsibilities

• Plan, design, develop, and own the platform’s management API — the self-service interface through which client teams create and configure search systems, manage ingestion topologies, register reusable components, promote index versions, and monitor system health — resolving problems of diverse scope with innovative thinking and little or no precedent to guide solutions.
• Arcitect the platform’s multi-tenant access model: implement strict data isolation between client tenants, integrate with enterprise identity providers, establish role-based access control across all API endpoints, and define the governance framework that ensures the platform can make credible security commitments to enterprise customers.
• Design and expose the API surface required to support the platform’s evaluation and experimentation workflows — including endpoints that enable the search grading tool to consume experiment run outputs, query/result pairs, and relevance judgments, and that allow client teams to configure and trigger A/B search experiments through self-service interfaces.
• Design the configuration data model and persistence layer (DynamoDB and related services) that stores search system definitions, component registry entries, index lifecycle state, and audit logs — applying architectural patterns that scale to the platform’s multi-tenant and multi-region ambitions.
• Break down complex business requirements into functional and technical requirements with consideration for security, ethical AI implementation, and operational efficiency; contribute to recommendations where technology transformation can spark business growth.
• Own infrastructure cost management: monitor AWS spend across platform components, evaluate architectural trade-offs at the system level, and implement an enterprise performance and optimization framework that keeps the platform’s economics sustainable as it scales — including compute cost governance for inference workloads as custom model serving is introduced.
• Implement and operate customer-controlled encryption key (CMK) support — applying security strategy, risk assessment frameworks, and security governance to give enterprise clients control over their encryption keys while preserving multi-tenant reliability.
• Define and own platform-level SLOs covering API availability, query latency, ingestion throughput, and end-to-end document freshness — and build the monitoring infrastructure (CloudWatch, distributed tracing, alerting) that makes SLO compliance continuously visible to the team and to client teams.
• Design the observability infrastructure for agentic retrieval paths — where standard request/response logging is insufficient: implement trace-level instrumentation that captures tool invocation sequences, per-hop latency, and retrieval inputs, enabling reliable diagnosis of failures and quality regressions in non-deterministic agent workflows.
• Take full operational responsibility for platform API and infrastructure — you built it, you own it, you run it: triage and resolve incidents, write thorough post-mortems, and drive systematic improvements that prevent recurrence.
• Embed security architecture throughout the platform’s infrastructure: least-privilege IAM, secrets management, encryption at rest and in transit, audit logging, and compliance implementation aligned with TR’s enterprise security requirements.
• Lead significant projects and business initiatives that span multiple engineers and interact with partner teams; determine work priorities and make adjustments to short-term priorities while maintaining strategic focus; provide specialist advice to senior management on complex infrastructure and security issues.

Qualifications

You’re an ideal fit if you have:

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of software engineering experience, with demonstrated progression to staff-level or equivalent technical leadership — including ownership of a functional area and leadership of significant cross-functional projects.
• Deep expertise in cloud-native platform and infrastructure engineering on AWS: VPC architecture, IAM, ECS, Lambda, DynamoDB, MSK, and related managed services — with hands-on infrastructure-as-code experience (Terraform and/or AWS CDK) and the ability to establish infrastructure governance frameworks.
• Production experience with OpenSearch, Vespa, or Elasticsearch at an operational level — cluster sizing, backup and restore, index lifecycle management, and multi-tenant access controls.
• Mastery of Python with strategic awareness of language selection and migration; strong software engineering fundamentals including testing architecture, security architecture, and system design.
• Experience operating Kafka (MSK) or other distributed messaging infrastructure in production, including partition management, consumer group monitoring, and schema registry governance.
• Experience building developer-facing internal platforms where API quality and documentation are treated as first-class product concerns.
• Familiarity with distributed tracing infrastructure for non-deterministic or agentic workflows — where trace design must capture tool call sequences and per-hop context, not just request/response pairs.
• Knowledge of enterprise encryption patterns, including customer-managed keys (AWS KMS) and their architectural implications for multi-tenant systems.
• Experience with Kubernetes or ECS container orchestration, including service mesh, autoscaling, and health check patterns.
• Experience with AI-assisted development tools; you use them to move faster and produce higher-quality infrastructure and API code, and you actively help the team do the same.