TrustIn
About the Role
The Role
You’ll sit at the intersection of backend engineering, infrastructure and distributed systems, owning the services and platform that power real-time data querying and AI agents.
You will:
Design and build backend services and APIs that connect to data warehouses, BI tools and SaaS systems.
Own infrastructure and reliability across AWS/GCP (or similar): container orchestration, networking, security, deployments.
Architect and operate high-throughput data and query pipelines for analytics workloads.
Implement robust observability (metrics, logs, tracing, alerting) and help shape SLOs and on-call.
Work closely with ML / product teams to turn prototypes of “AI data analysts” into reliable, scalable production systems.
This is a proper ownership role: you’ll make key decisions on architecture, tooling and operational standards.
What You’ll Work With
You don’t need every bullet, but this is roughly the stack and environment:
Languages: Python, Go or TypeScript/Node for backend services.
Cloud: AWS or GCP; VPCs, load balancers, IAM, secrets, etc.
Infra: Docker + Kubernetes (or ECS/Nomad equivalent), Infrastructure-as-Code (Terraform/Pulumi).
Data: Warehouses (Snowflake/BigQuery/Redshift), PostgreSQL, analytical query engines.
Observability: Prometheus / OpenTelemetry / Datadog or similar.
CI/CD: GitHub Actions / GitLab CI or equivalent, with automated testing and rollouts.
Requirements
Location: San Francisco Bay Area
Compensation: Top-of-market salary + meaningful equity
Role type: Backend Engineer / Infrastructure Engineer / Systems Engineer
What They’re Looking For
4+ years as a Backend Engineer, Infrastructure Engineer or SRE in a product environment.
Strong experience designing and running distributed backend systems in production.
Hands-on with at least one major cloud provider and Kubernetes / container orchestration.
Confident with SQL and working against warehouses / transactional stores at scale.
Comfortable owning systems end-to-end: design → implementation → deployment → monitoring → incident response.
Enjoy partnering with product and data/ML folks, not just sitting behind tickets.
Nice to have
Background in data / analytics / BI platforms or similar.
Experience with RBAC, multi-tenant architectures and enterprise security.
Prior time in a high-growth startup or as an early engineer.
Why This Role Is Attractive
Real impact: You’re building the platform that lets non-technical teams query complex data with natural language.
Big surface area: Backend, infra, data systems and reliability – not just one narrow microservice.
Senior peers: Small, highly-technical team with strong backgrounds in data, infra and AI.
Upside: Competitive compensation and equity in a company at the heart of the AI + data wave.
About the Company
High-growth AI data platform helping enterprise teams query and understand their data through conversational “AI data analysts”. Think: semantic layer + agents + natural language over warehouses and BI tools.
They’re well-funded, selling into serious mid-market / enterprise customers, and now hiring a Backend Infrastructure / Systems Engineer to harden and scale the core platform