We're building an AI-native B2B platform that processes complex business data, runs document intelligence pipelines, and surfaces insights through LLM-powered workflows. The product is live, serving real clients, and the surface area for testing is genuinely interesting: async job workers, non-deterministic AI outputs, multi-process backends, and a PWA frontend.
You'll learn to be the engineer who ensures none of it breaks quietly.
About Us - Ekam Apps
Ekam Apps (ekamapps.com) is a lean, AI-first studio that builds products and automation solutions for clients across industries. Our daily workflow runs on AI-native tools and Claude: that is how we ship fast with a small team.
We build and run two AI products of our own:
- Docwise: an AI-powered document intelligence platform for automated collection, verification, and processing of documents across WhatsApp, email, and branded portals. Covers 50+ document types with 800+ government source verifications, all no-code.
- ComWise: an AI-powered customer engagement platform that brings WhatsApp and web chat into a unified inbox with an AI copilot, workflow automation, and campaign tools. Backed by Claude, Gemini, and GPT.
We work with clients ranging from an Australian public-sector intelligence platform to Indian fintech and insurance companies. Real products, real users, real impact.
Nitin Gupta, Founder, 20+ years in tech, 12+ in leadership across India Today Group, Lenskart, Senior World, and Zecross.
The Role - Quality is engineering here, not a checkbox
This is not a manual testing role with some automation on the side. You'll be writing code: building test frameworks, designing coverage strategies for AI pipelines, and integrating automated suites into CI/CD. You'll work directly with the full stack developer to catch issues before clients do.
Testing an AI product has its own challenges. LLM outputs are non-deterministic. Document parsing can behave differently across PDF formats. Background job workers fail in ways that don't always surface immediately. You'll need to think about how to verify correctness when correct isn't always a fixed string. That means building eval frameworks: structured ways to measure AI output quality across dimensions like relevance, accuracy, consistency, and hallucination rate, so regressions surface before clients do.
Responsibilities - What you'll own
- Design and build the end-to-end test automation framework from the ground up
- Write and maintain automated tests across API, integration, and UI layers
- Build test strategies for AI features: LLM output evaluation, prompt regression, document processing accuracy
- Design and maintain eval frameworks to measure AI output quality: relevance, accuracy, consistency, and hallucination detection across prompt changes and model updates
- Test async pipelines and background job workers (queue processing, retry logic, failure scenarios)
- Set up and own the CI/CD quality gates: test runs, coverage thresholds, and failure reporting
- Conduct performance and load testing on API endpoints and job processing systems
- Write test cases for PostgreSQL-backed data flows and validate schema migrations
- Build regression suites that run on every deploy and catch regressions before release
- Work closely with the developer to identify testability gaps early in the build cycle
- Maintain test environments and seed data strategies for consistent, repeatable test runs
What We're Looking For - Strong fundamentals and a genuine curiosity to learn
- Fresh graduate or up to 2 years of experience in software testing or development
- Basic programming ability in JavaScript, Python, or any scripting language: you can write a loop, read a stack trace, and figure out what broke
- Foundational understanding of software testing concepts: test cases, regression, functional vs. non-functional testing
- Exposure to API testing tools like Postman or REST clients, even if through coursework or self-learning
- Comfortable with SQL basics: reading a query result and checking whether the data looks right
- A genuine interest in AI and curiosity about how to verify outputs that are not always black and white
- Methodical and detail-oriented: you notice things others miss, you document what you find, you ask good questions
- Eager to build, not just run: you want to write the automation, not just execute test cases someone else wrote
Nice to Have - Bonus points
- Experience testing LLM-powered features or building evals for AI outputs
- Familiarity with Supabase, PostgREST, or row-level-security testing
- Performance testing experience with tools like k6 or Artillery
- PWA or service worker testing experience
- Worked on a product with multi-process backend architecture
- Contributed to test infrastructure as code (fixtures, factories, seed scripts)
What we offer
Annual Package - ₹3.6 – 4.5 LPA
Depending on experience
Role Type - Full-Time
Quality ownership from day one
For freshers: first 3 months on a probation stipend of ₹10,000–15,000/month, followed by full salary on confirmation.
Before You Apply - This role is right for you if...
- You are comfortable working remotely and can stay productive and accountable without a structured office environment
- You are genuinely interested in quality engineering as a craft, not just looking for a testing role as a fallback
- You are willing to commit to at least a year: building a test framework from scratch takes time, and we need someone who will see it through
- You can handle startup pace: priorities shift, requirements evolve, and some days you will need to debug something nobody has seen before. That should excite you, not frustrate you
- You want direct access to the founding team and the client, with real say in how quality is approached on the product
