About Anosys

Anosys helps teams understand and improve AI systems in production. Our platform connects observability, agent traces, evaluations, cost, and user behavior with business outcomes, helping organizations investigate problems, identify opportunities, and make better operational and product decisions.

We are expanding our engineering team to advance the platform’s capabilities and support growing customer workloads with reliable, efficient systems.

About the Role

As a Senior Backend Engineer — Data Platform, you will evolve and operate the services that ingest, process, store, and serve data across Anosys. You will take ownership of defined backend services, from technical design and implementation through deployment and production operation.

Your work will help customers trust their data and use the platform effectively as workloads grow. You will address practical challenges in data correctness, service reliability, query performance, tenant isolation, and infrastructure efficiency, making tradeoffs based on measured needs.

You will work closely with the engineering, product, applied science, and solutions engineering teams to translate customer needs into maintainable production systems. This is a hands-on role for an engineer who combines strong implementation skills with sound architectural judgment and follows work through to its operational impact.

What You’ll Do

• Evolve core data services. Design and improve the ingestion, processing, storage, and API services that support observability and analytical workflows.
• Protect data correctness. Account for retries, duplicate and out-of-order events, schema changes, and partial failures. Make data behavior understandable and recovery procedures dependable.
• Strengthen reliability and tenant isolation. Improve how services handle workload spikes and resource contention, and maintain appropriate boundaries between customer data and workloads.
• Improve performance and efficiency. Investigate bottlenecks, benchmark representative workloads, and optimize processing, storage, and query paths with attention to infrastructure cost.
• Deliver dependable APIs. Develop clear service interfaces and manage compatibility, validation, access controls, and error handling as the platform evolves.
• Own production outcomes. Instrument services, define meaningful service objectives with the engineering team, contribute to capacity planning, and participate in incident response and follow-up improvements.
• Make changes safely. Use automated tests, representative load testing, controlled rollouts, and recovery plans to reduce risk when changing services or data models.
• Collaborate across teams. Partner with the product and applied science teams to integrate capabilities into reliable services, and with the solutions engineering team to investigate recurring customer issues.
• Raise engineering quality. Contribute thoughtful design and code reviews, document important decisions, and help the engineering team choose practical approaches to evolving requirements.

What We’re Looking For

• Significant experience developing and operating production backend systems, typically gained through 5+ years of software engineering. We value demonstrated ownership and technical depth alongside years of experience.
• Strong proficiency in at least one backend language, such as Python, Go, or Rust, and the ability to work effectively in an existing codebase.
• Hands-on experience with data pipelines, asynchronous processing, or streaming systems, including troubleshooting their behavior under failure and load.
• A practical understanding of distributed systems concepts such as partitioning, replication, consistency, backpressure, and idempotency, and the judgment to apply them appropriately.
• Experience working with databases and analytical workloads, including data modeling, query optimization, and storage tradeoffs.
• Experience deploying and operating services in a cloud environment, with familiarity with containers, automated delivery, and infrastructure configuration.
• A strong approach to testing and debugging. You can reproduce failures, use telemetry to investigate causes, and validate that a change solves the underlying problem.
• Awareness of security and data-access requirements in multi-tenant software, including authorization and isolation boundaries.
• The ability to make and explain tradeoffs among reliability, performance, complexity, delivery time, and cost.
• Clear communication, collaborative problem-solving, and a willingness to take responsibility for systems after they reach production.

Experience That Would Be Especially Valuable

• Working on observability, developer tooling, product analytics, or other data-intensive SaaS platforms.
• Experience with OpenTelemetry, distributed tracing, event schemas, or telemetry data modeling.
• Depth in streaming infrastructure or columnar and time-series databases.
• Improving performance and infrastructure efficiency using production measurements and representative benchmarks.
• Integrating analytical or machine-learning workloads into production services in collaboration with applied science teams.
• Managing backward-compatible API changes, data migrations, or service recovery in customer-facing systems.
• Improving engineering practices and sharing technical knowledge within a growing team.

What Success Looks Like

The services you own behave predictably, recover reliably, and make their health visible. Customers can trust the data they use, and the engineering team can make changes with confidence.

Your work produces measurable improvements in reliability, performance, or efficiency against agreed baselines. Recurring incidents and operational toil decrease, and technical decisions remain understandable to the teams maintaining the platform.

How We Work

We value clear reasoning, practical solutions, and ownership. We investigate before optimizing, test assumptions against evidence, and choose complexity deliberately.

You will collaborate with the engineering, product, applied science, and solutions engineering teams, with meaningful responsibility for improving the platform as Anosys grows.