QA Engineer

AI Product QA Engineer

This is not the QA you know. We're not hiring someone to find bugs. We're hiring someone to guard the user's experience — with AI as the foundation.

Read this before you read anything else

Forget everything traditional QA taught you.

I don't want "I tested it, here are the 14 defects." I don't want a gatekeeper at the end of the line ticking checkboxes against a technical feature list. That QA is dead here, and honestly, AI already does it better.

I want business-product QA. Product taste as a discipline. User empathy as a test case. Your foundation is AI — everything runs through Claude Code / Codex — and on top of that foundation you apply QA from a business, user-empathy, onboarding, and go-to-market lens. You're not asking "does the button work?" You're asking "is this the sharpest user journey this product could possibly have?"

We're extreme about four things and nothing else: extreme hard work, extreme respect, extreme shipping, extreme innovation. Not hours . There's no boss — there's a product, a user, and you. You're rewarded on one thing: your hunger.

The 90 / 10

Same philosophy that runs this whole company. 90% of the work, AI does. Claude Code writes the test cases, automates the suites, drives the API calls, spins up the harness — faster than any QA team I've ever run . That 90% is the floor now.

The 10% is you — the human who decides what's actually worth testing and why:

• the user empathy — feeling the friction a real brand manager feels at 9pm
• the judgment — is this the sharpest journey, or just a working one?
• the taste — the design standard, the elegance, the delight
• the business sense — does this survive a real client's Tuesday, their onboarding, their objection?
• the critical eye — reading an AI trace and knowing instantly when the product is confidently wrong

AI didn't shrink QA. It concentrated it. The 10% is smaller and heavier than the 100% ever was. That's the 10% I'm hiring.

How you actually work

Everything you do runs through Claude Code. You write the cases in it. You automate the cases in it. You do business testing in it. You interrogate user empathy in it — "how will the user react to this, and is this the sharpest journey of the product?"

But make no mistake: this is technical QA. You write scripts. You hit and test APIs directly. You read the traces, the payloads, the failure modes. You don't wait for a UI to click — you go straight at the system. The difference from old-school QA isn't less technical; it's technical in service of the user and the business, not the feature checklist.

The stack & the surface

We're a web application in Python, Rust, and everything in between — and you'll be QA-ing across four products: ARIA, the Persona product, the video-decoding product, and the rest of the family. Real APIs, real pipelines, real agents watching millions of social videos in Hindi, Tamil, Bahasa, Thai for the world's biggest consumer brands . You need to be comfortable writing a script to probe any of them and reading exactly what came back.

Your first 48 hours

Day one, morning: you get access to a live product and its real client questions in the queue. Not a sandbox. Not a tutorial.

Day one, afternoon: you pick one user journey and, in Claude Code, you build the case, automate it, and pressure-test it against the actual experience a client would have.

Day two: you tell me not "here are the defects" but "here's where the journey breaks the user, and here's the sharper one." And you've already got the automated eval that guards it going forward.

If that scares you, this isn't your room. If it makes you grin — keep reading.

The loop

We are always on. A technique drops on Twitter Tuesday morning; by Thursday it's in a product; by Friday a brand team on the other side of the world is using it — and someone has to make sure that journey is delightful, not just functional. That someone is you. See it. Test it against the user. Sharpen it. Ship it. The loop never stops. If your learning lives in "read later" folders , this will break you.

What you own

The user's experience across every product. Not the defect list — the journey. Find a problem and you don't just log the instance; you build the automated eval in Claude Code that kills the whole class of bad experience forever. Your evals become the product's conscience. Your standard becomes the bar the whole team ships to.

The bar is craft, not years. 23 or 43 — I don't care. I care whether you can feel what a user feels and write the script that proves it.

Who this is actually for

This is a close-to-100% self-starter environment.

You do not want to be here if you want to be handed a test plan. You want to be here if you believe you're the only one who can guard this product's soul — the king or queen of the user journey — with absolute hunger burning in you to do it. Here, will is bigger than skill. And AI isn't a tool you use; it's the foundation you think on.

Fair warning ⚠

The pace is relentless and there's no playbook for AI-product QA — you're partly inventing the discipline as you go. If you want a stable checklist and a comfortable gate at the end of the pipeline, you'll be miserable here, and I'd rather you know now. But if you want to define what QA even means in the age of agents — what you learn here in one year, you won't learn anywhere else in five.

How this goes

Don't send a resume. Send the 10%.

An eval harness you're proud of. A test suite you built in Claude Code that caught something a checklist never would. A teardown of a product's user journey where your taste and your technical chops were unmistakably yours.

Work Location: Remote

Key Responsibilities

1. Platform & Application Architecture

• Architect and oversee end-to-end platform design using GCP services (Vertex AI, Cloud Run, GKE, Pub/Sub, Firestore, BigQuery, and IAM).
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• Define the architecture for multi-tenant SaaS deployment—ensuring secure data boundaries across customers while maintaining a single codebase.
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• Collaborate closely with backend developers to optimize Node.js APIs, data pipelines, and event-driven microservices.
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• Design front-end integration flows and ensure UI/UX alignment with backend AI and agentic processes.
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2. AI / LLM / Agentic System Architecture

• Lead architecture for all AI initiatives involving RAG pipelines, AI agents, NLP, and conversational AI.
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• Evaluate and integrate LLMs and APIs from OpenAI, Google Gemini, Anthropic (Claude), Mistral, and others.
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• Define frameworks for AI agent orchestration, prompt engineering, and function/tool calling workflows using frameworks like LangChain or LlamaIndex.
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• Establish standards for vector databases (Pinecone, FAISS, Chroma), embeddings, chunking strategies, and retrieval optimization.
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• Architect an AgentOps layer for monitoring, safety filtering, and AI model governance.
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3. MLOps, PromptOps & DevOps Integration

• Implement CI/CD pipelines for AI models, prompts, and agents using Cloud Build, Terraform, and GitHub Actions.
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• Design PromptOps and MLOps pipelines to manage model lifecycle, versioning, rollback, and production promotion.
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• Define observability and monitoring mechanisms (OpenTelemetry, Cloud Monitoring, custom logs for LLM outputs).
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• Collaborate with DevOps engineers to define blue/green and canary deployments across environments.
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4. Security, Compliance & Scalability

• Design tenant-isolated data layers using IAM, VPC-SC, and KMS encryption policies to meet regulatory standards (HIPAA, GxP, GDPR).
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• Implement data governance, access control, and threat detection mechanisms for AI-driven workflows.
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• Create performance optimization strategies: GPU/TPU allocation, autoscaling policies, token budgets, response caching, and FinOps visibility.
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5. Cross-Functional Leadership

• Partner with Product Managers and Business Analysts to translate business requirements into architectural blueprints.
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• Work with UX/UI designers to ensure front-end experiences align with AI agent capabilities and backend APIs.
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• Provide architectural guidance and technical mentorship to developers, ensuring adherence to best practices across projects.
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• Contribute to platform evolution, reference architecture libraries, and reusable design patterns.
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Key Skills & Qualifications

Technical Expertise

• Strong background in cloud architecture, specifically Google Cloud Platform (GCP)—Vertex AI, Cloud Run, Cloud Storage, IAM, Pub/Sub, BigQuery, VPC, and Cloud Functions.
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• Proficiency with Node.js, TypeScript, and API development for scalable microservices.
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• Deep understanding of LLMs, AI agent frameworks, retrieval-augmented generation (RAG), and vector search.
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• Experience with LangChain, LlamaIndex, CrewAI, and Agentic AI design patterns.
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• Strong understanding of data architecture, including NoSQL/SQL databases (MongoDB, Firestore, PostgreSQL).
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• Hands-on experience with container orchestration (Docker, Kubernetes) and Infrastructure-as-Code (Terraform).
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Preferred Skills

• Prior experience designing multi-tenant SaaS platforms.
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• Exposure to frontend integration (Angular, React, or similar) and UI/UX flow understanding.
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• Knowledge of AI safety, risk frameworks, and prompt governance.
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• Strong analytical and communication skills for working across business and technical stakeholders.
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• Awareness of FinOps and cost optimization in token-based AI ecosystems.
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Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or Cloud Architecture.
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• 8–12 years of professional experience, with at least 3 years focused on AI platform architecture or enterprise-grade SaaS system design.
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Certifications in GCP Professional Cloud Architect or Machine Learning Engineer are a plus.

Key Responsibilities & Job Duties

● To provide functional support for our ERP

Finance applications (Oracle eBusiness Suite)

○ Assist users in case of question

○ Manage functional requests

● Train users to keep the right level of skill

○ To organize audits of the use of systems

○ Detect and collect issues

○ Implement action plan and coordinate actions

● To manage enhancements in accordance with the procedures which apply in the department

○ Collect enhancements from users

○ Challenge the user requirements

● Define priorities

○ Write functional specifications and coordinate developments with the technical team

● Test and train the users

○ Regularly communicate to the users the status of the enhancement

○ Report activity to the management

○ Collaborate with functional support in other zones to share information

○ Optionally, may manage some projects

Key Technical & Functional Competencies
● Functional competencies

○ Strong Business processes: Finance

● Technical competencies

○ Good Knowledge of Oracle SQL

○ Strong Oracle eBusiness Suite

Modules: AP, AR, GL, FA (At least at a professional for two Modules)

○ Basic knowledge of Oracle eBusiness Suite Modules: INV, PO, OE, WSH is preferable

Lead a team of software developers to deliver customer requirements,

on time, within budget while ensuring high level of quality.

● Tracking a project against schedules and taking corrective actions on

slippage. Escalation to the next level in case of slippage / likely slippage

in time or quality parameters.

● Manage the relationship with the client and relevant stakeholders

● Regular coordination with clients, internal resources and third

parties/vendors for the flawless execution of the project

● Ensure that all projects are delivered on-time, within scope and within

budget

● Assist in the definition of project scope and objectives, involving all

relevant internal stakeholders and ensuring technical feasibility

● Develop a detailed project plan to monitor and track progress

● Report and escalate to management as needed

● Perform risk management to minimize potential risks

• ● Prepare / review project documents such as FSD / FRD

• NLP 

• ML programming
• Spark
• Model Deployment
• Experience processing unstructured data and building NLP models
• Experience with big data tools pyspark
• Pipeline orchestration using Airflow and model deployment experience is preferred

Required Candidate profile

Job Purpose:

To Answer queries/resolve problems of customers through Inbound.

Attend Inbound & Outbound calls, sometime respond through email and chat to customers.

Provide correct and quality information to customers on every call, promote good listening and English grammar skills.

Eligibility Criteria:

Good speak, read & Write English & Hindi mandatory.

Able to communicate confidently and politely, with good speaking skills.

Awareness on Banking or Banking products.

Detailed knowledge of intricacies of Banks products and how they compare against competitors.

Good typing skills (Quality & Speed)

Ability to handle telephonic conversations

Good Listening & Comprehension skills

Should be flexible to work in 24/7 shift