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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Backend Engineer - **Company:** SimilarWeb LTD - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Query Performance, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Business Analytics Applications, User Authentication, Big Data, BigQuery, Code Generation, Software Quality, Databases, Concurrent Computing, Continuous Integration, Data Integrity, Data Security, Cursor, Software Debugging, Distributed Systems, Fault Tolerance, Python (Programming Language), PostgreSQL, Online Analytical Processing, Node.Js, Query Optimization, Microsoft Copilot, Systems Architecture, TypeScript, Management of Software Versions, Datadog, Data Logging, ReactJS, Istio, Large Language Models, Claude Code, Snowflake, Prompt Engineering, Caching, AI Coding Agents, Backend, Agentic-AI, Fastapi, Build Management, Kubernetes, Low Latency, Data Management, Front End Software Development, Vertica, Api Design, NestJS, Model Context Protocol, Dynatrace, Api Management, Docker - **Published:** October 19, 2026 - **Apply:** https://job-boards.greenhouse.io/similarweb/jobs/8299494 ## About the Role * 5+ years of backend engineering experience, building and operating production services at scale * Strong proficiency in Python (FastAPI or an equivalent async framework) or in Node.js/TypeScript (NestJS) - with genuine willingness to work in both; our services run on each * Experience designing scalable backend architectures, clear service boundaries, and data models that survive their second use case * Deep understanding of API design, authentication and authorization flows, and distributed system tradeoffs * Strong command of async and concurrent programming, and of long-running or distributed execution (workflow engines, queues, schedulers) * Experience with relational and/or analytical databases, including schema design, migrations, and query optimization * A track record of making queries fast and cost-efficient over large datasets - PostgreSQL at scale, or an OLAP/columnar engine such as Athena, Firebolt, BigQuery, Snowflake, or ClickHouse. The engine is learnable; the instinct for scan cost and data volume is what we are hiring for * Strong understanding of system performance, reliability, and security best practices * Experience with testing methodologies (unit, integration, E2E) and observability tooling - metrics, structured logs, distributed tracing * Comfort owning the runtime: Docker, Kubernetes, and CI/CD pipelines * Production experience putting LLM or model APIs inside a backend service, treating latency, failure modes, cost, and non-deterministic output as engineering problems rather than demo caveats * Hands-on experience using AI development tools in daily workflows, with the ability to validate, debug, and improve AI-generated code * Understanding of prompt engineering for engineering workflows and the ability to work effectively in fast iteration environments * Strong product and technical intuition, with excellent communication and collaboration skills * Enough frontend fluency (React, TypeScript) to reason about how your APIs are consumed - you will not own the UI, but you will design for it * Nice to have: agent orchestration frameworks (LangGraph, LangChain) or the Model Context Protocol; a durable workflow engine (Temporal, Airflow, Step Functions); data platforms, analytics products, or BI tools ## Description This role combines deep backend and distributed systems expertise with product thinking and the ability to leverage AI tools effectively across the development lifecycle. You will work closely with product, design, frontend, and data/AI teams to build reliable, performant services, while driving engineering excellence and modern development practices. Your contributions will shape the technical foundation of an AI-first product and directly influence what end users can ask of it. What does the day to day of a Senior Backend Engineer at Similarweb look like: Your daily work will span service architecture, data access at scale, workflow orchestration, and AI-augmented development, engaging directly with the systems that power our product. Your role will include: * Design and build scalable, maintainable backend services in Python (FastAPI, Pydantic, asyncio) and TypeScript (NestJS / Node.js) * Own API design, contracts, and versioning across services - including the tool surfaces (MCP) our AI agents call directly * Design and optimize data models, schemas, migrations, and query performance across transactional (PostgreSQL) and large-scale analytical stores (Firebolt, Athena, DuckDB) * Build and operate asynchronous, long-running execution: durable workflow orchestration (Temporal), queues, scheduled jobs, and event-driven processing * Integrate LLM and agent runtimes (LangGraph, MCP, model APIs) into production services behind deterministic, testable boundaries * Implement authentication, authorization, and secure service-to-service integration patterns across an internal service mesh * Build resilient upstream data-fetching layers: timeouts, retries with backoff, caching strategies, and graceful degradation when a source is slow or down * Lead backend technical decisions, code quality standards, and system architecture * Ensure system scalability, fault tolerance, and observability - structured logging, metrics, distributed tracing, and alerting that makes production debuggable * Own services end to end in production: CI/CD pipelines, containerized deployments to Kubernetes, and the debugging that follows * Partner with frontend engineers on API contracts, data shapes, performance budgets, and UX constraints - designing for the consumer without owning the UI * Translate product requirements into robust, scalable technical solutions, working closely with product and design * Conduct high-quality code reviews and drive architectural discussions and best practices * Improve testing across the pyramid - unit, integration, and end-to-end against real service stacks - alongside observability and reliability * Use AI coding tools effectively in daily development work (Claude Code, Cursor, Copilot, etc.), critically evaluating and refining AI-generated code, especially for backend logic and data integrity * Design efficient personal/team workflows for AI-assisted development and contribute to engineering productivity through AI tooling and automation