Lead Engineer, Backend and Infrastructure

Location: Surat, Gujarat

Work mode: Full-Time (WFO)

About TestDino

TestDino (testdino.com) is the AI-native Playwright test intelligence platform: teams debug, manage, and ship Playwright tests in CI at scale. Our reporter streams results, traces, screenshots, and videos to the dashboard in real time, our ML engine classifies failures and scores flaky tests across millions of executions, and our MCP server gives AI agents direct access to test context. Engineering teams tell us we save them 6 to 8 hours per engineer every week.

We are SOC 2 Type 2 and ISO 27001 certified, GDPR compliant, and run on Microsoft Azure with a 99.9% SLA for enterprise customers. Customers range from quick-moving startups to enterprises replacing TestRail and Currents.

The role

You will own the backend and infrastructure of the platform: a TypeScript microservices monorepo behind a real-time ingestion pipeline that processes test artifacts from thousands of CI runs a day. You will be the most senior engineer on this surface, set its technical direction, and ship on the roadmap that customers are waiting for: auto-quarantine for flaky tests, smart test orchestration, a public API, and agentic test management.

What you will do

- Scale the ingestion pipeline: real-time streaming of results, traces, screenshots, and videos from customers' CI (GitHub Actions, GitLab, Azure DevOps, Jenkins, TeamCity, CircleCI, Bitbucket, CodeBuild) with spiky, high-volume load.
- Own the microservices monorepo: user, ingestion, data-handler, tcm, ai-insight, billing, integration, and mcp services, plus the Next.js product frontend, in a pnpm workspace on Postgres.
- Run and evolve our Azure infrastructure: containerized services behind Nginx, CI/CD, observability, capacity, and cost.
- Keep enterprise auth solid: RS256 JWTs with rotating refresh sessions, SAML 2.0 SSO, SCIM provisioning, personal access tokens, API keys, and org management.
- Build the AI side of the product: the ai-insight service, failure classification,



the flaky-detection ML pipeline, and the TestDino MCP server (33 tools, built on the Model Context Protocol SDK).
- Uphold the controls behind our SOC 2 Type 2 and ISO 27001 certifications in day-to-day engineering.
- Ship customer-facing npm packages when needed: the @testdino/playwright reporter and CLI (tdpw).

Our stack (what you will actually touch)

- Languages and runtime: TypeScript end to end, Node.js 18+.
- Services: pnpm monorepo of nine services, REST APIs, Next.js (product app and marketing site), Apollo GraphQL on the website.
- Data: PostgreSQL, object storage for traces and media, real-time streaming ingestion.
- Infrastructure: Microsoft Azure, Docker containers, Nginx reverse proxy, CI/CD, encryption at rest (AES-256) and in transit (TLS 1.2+).
- Testing domain: the Playwright ecosystem, CI providers listed above, JUnit/CTRF-style artifacts.
- AI product surface: Anthropic Claude APIs, Model Context Protocol (MCP) SDK, ML-based flaky detection, n8n integration.

AI tools are how we work, not a bonus We are an AI-first engineering team and expect the same fluency from you:

- Claude Code as a daily driver: you know how to structure work with subagents, write and use skills (slash commands), configure hooks, and wire up MCP servers. You know what an agent harness is and when to reach for the Claude Agent SDK versus a plain API tool-use loop.
- Building with the Anthropic API: Messages API, tool use, streaming, prompt caching, and designing agent loops that are cheap and reliable in production.
- Agent infrastructure: we run an internal AI teammate with org-wide memory and per-session Docker sandboxes, and our product ships an MCP server to customers.



You should be comfortable designing sandboxed agent execution, memory/context systems, and token-scoped credentials.
- You treat prompts, agent configs, and evals as engineering artifacts: versioned, reviewed, and tested.

What we are looking for

- 6+ years building backend systems in production, with 2+ years owning infrastructure or platform surfaces; you have been the person paged when ingestion fell over, and you fixed the class of problem, not the instance.
- Deep TypeScript/Node.js experience at scale, including performance work on Postgres (query plans, indexing, partitioning).
- Real cloud operations experience; Azure preferred, but strong AWS/GCP experience transfers.
- You have built or run event-driven or streaming pipelines with real throughput and backpressure concerns.
- Security instincts: you have implemented SSO/SCIM or equivalent enterprise auth, and you can work inside SOC 2/ISO 27001 controls without slowing down.
- The Claude fluency described above, demonstrated with something you have actually built.

Nice to have: test-infrastructure domain experience (Playwright, CI at scale, test reporting), applied ML for classification or anomaly detection, published npm packages, open-source contributions.

How we work

- Small senior team, direct access to the founder, and to customers: engineers join sales and support calls, and customers regularly see their feedback shipped within weeks.
- We write things down: internal docs, customer docs (docs.testdino.com), and runbooks.
- Concrete over impressive: in code review and in writing, every claim should be checkable.

Process

1. Intro call (30 min): your background, our roadmap.
2. Technical deep-dive (60 to 90 min): walk us through a system you own; then a design discussion on an ingestion or agent-infrastructure problem from our world.
3. Practical exercise (take-home or pairing, your choice): includes using Claude Code the way you would on the job.
4. Founder conversation and offer.

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