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Qapitol QA

Careers — Build AI Quality Engineering's Future | Qapitol

Do the work that defines AI quality.

At Qapitol, you'll build the tools, platforms, and methodologies that help the world's most important AI systems be reliable, fair, and compliant. Real problems. Real impact. Real team.

View Open Roles →

01

350+

Team members

02

4.6★

Glassdoor rating

03

94%

Would recommend

04

₹4L

Learning budget/year

05

45 days

Annual leave

06

13

Open roles

What you'll actually work with

We're an AI-native team. You'll work with real AI systems in production for real enterprises — not toy demos.

  • LLM / GenAI: OpenAI GPT-4o, Anthropic Claude, Gemini, Llama 3, custom fine-tuned models
  • Eval & Testing: QAVE (our own), RAGAS, DeepEval, PromptFlow, custom eval harnesses
  • Agentic: LangChain, LangGraph, CrewAI, AutoGen, custom agent frameworks
  • MLOps: MLflow, Weights & Biases, DVC, BentoML, Seldon
  • Data & Pipelines: Apache Airflow, dbt, Spark, Databricks
  • Infrastructure: AWS (SageMaker, Bedrock), Azure ML, GCP Vertex AI, Docker, Kubernetes
  • QE & Testing: Selenium, Playwright, RestAssured, K6, custom AI test frameworks
  • Governance: CHEQ (our own), regulatory obligation libraries, policy engine

We're building something that matters. Here's how we do it.

Our culture pillars.

  • AI-native from day one: Every team member has access to Claude, GPT-4, Gemini, and our own QAVE and Nexus platforms. We use AI to accelerate our own work — and build products that do the same for our clients.
  • Craft matters here: We care deeply about quality — in our code, our delivery, our thinking. This is a company built by practitioners who take their craft seriously. If that's you, you'll fit right in.
  • Hybrid-first, async-friendly: Work from where you do your best thinking. We have offices in Hyderabad and Bengaluru with flexible hybrid arrangements. Strong async culture with documented decisions and clear context.
  • Grow fast or go deep: Qapitol is growing quickly. You can grow fast with it — into leadership, into new practices, into new domains. Or go deep into an area of expertise and become one of the best in the industry.
  • No nonsense, high trust: Low hierarchy, high ownership. We don't micromanage. We set context and let smart people make good decisions. When you mess up, we learn and move on. When you win, it's visible.
  • Front-row seat at the AI revolution: You'll work on real AI systems — eval pipelines, SLM fine-tuning, RLHF, compliance frameworks — before most of the industry understands these exist. It's a remarkable time to be here.

From the Team

Testimonials from current team members.

  • Sneha Raghavan, AI Evaluation Lead, 2 years at Qapitol: 'I joined Qapitol as a senior SDET and within 18 months I was leading the AI Evaluation pod. The growth trajectory is real — if you're willing to learn, the company will invest in you.'
  • Arjun Pillai, Senior SDET, 1.5 years at Qapitol: 'Coming from a traditional QE firm, I was worried about the pace. But Qapitol's culture is genuinely supportive — clear expectations, lots of context, and real mentorship from the practice leads.'
  • Divya Krishnamurthy, Compliance AI Engineer, 2.5 years at Qapitol: 'Working on CHEQ has been the most intellectually exciting thing I've done. Reading IRDAI guidelines and turning them into machine-checkable obligations — it's genuinely novel work.'

We take care of our people

Benefits at Qapitol.

  • Full AI Tool Stack — Claude Pro, GPT-4, GitHub Copilot, Cursor — all provided. Plus early access to QAVE, Nexus, and Agent Fabric.
  • ₹4L Learning Budget — Per year for courses, conferences, certifications, and books. No approval process for amounts under ₹25K.
  • Hybrid Working — 2–3 days in-office (Hyderabad/Bengaluru). Rest remote. Full work-from-home flexibility for deep work weeks.
  • Competitive CTC + ESOP — Market-leading compensation benchmarked to top-quartile QE/AI firms. ESOP participation for all tech roles from day one.
  • Health Insurance — ₹10L family floater for employee + spouse + children. Dental and OPD included. No waiting period.
  • Mental Health Support — Free access to counselling via YourDOST. No stigma — we talk about this openly and act on it.
  • 45 Days Leave — 25 earned leave + 12 sick days + 8 holidays. Plus maternity (26 weeks), paternity (4 weeks), and adoption leave.
  • Conference Speaking — We fund and actively encourage speaking at QE Conf, AI/ML conferences, and industry events. Travel + accommodation included.

Join the team building AI quality engineering's future — Open Roles

We're hiring across AI Engineering, Platform, GTM, and Delivery. All roles are hybrid (Hyderabad/Bengaluru) unless marked remote. Role filters: All Roles (13) | AI & Platform | GTM & Sales | QE Delivery.

  • ML Scientist — SLM Fine-Tuning & Alignment | Hyderabad | Full-time, Senior | AI Practice. We're building domain-specific Small Language Models for insurance, BFSI, and healthcare QE. You'll own the fine-tuning pipeline — from dataset curation through RLHF alignment to production deployment. You'll work on: fine-tuning Llama/Mistral/Phi models on domain-specific insurance and BFSI data; designing and running RLHF annotation pipelines with domain expert annotators; building evaluation frameworks for SLM performance on NER, classification, and reasoning tasks; contributing to our Policy Reasoning Traces (PRT) research. You bring: 3+ years ML engineering, experience with parameter-efficient fine-tuning (LoRA, QLoRA), strong Python, familiarity with regulatory or legal NLP a strong plus.
  • Senior AI Platform Engineer (QAVE) | Hyderabad | Full-time, Senior | Platform. You'll be a core builder on QAVE — our AI Simulation and Evaluation Engine. This is multi-tenant SaaS on Kubernetes, handling thousands of eval runs per day across LLM models and regulatory frameworks. Responsibilities: design and build eval pipeline orchestration (Python, FastAPI, Celery); multi-tenant K8s architecture — performance, isolation, cost efficiency; integrate QAVE with external LLM APIs (OpenAI, Anthropic, Gemini, Azure); build the on-prem / VPC deployment path for Enterprise Sovereign AI customers. You bring: 5+ years software engineering, strong Python/FastAPI, Kubernetes/Docker, experience with SaaS multi-tenancy, bonus for prior AI/LLM platform work.
  • DevOps / MLOps Engineer | Hyderabad | Full-time, Mid–Senior | Platform. Responsible for the infrastructure powering QAVE, Nexus, and CHEQ. You'll build and maintain the MLOps stack that enables our team to train, evaluate, and deploy AI models safely and at scale. Responsibilities: CI/CD pipelines for model training and platform deployment (GitHub Actions, ArgoCD); ML experiment tracking (MLflow), model registry, and deployment automation; monitoring and observability for AI systems in production (Prometheus, Grafana, OpenTelemetry); cost optimization across cloud GPU infrastructure. You bring: 4+ years DevOps/SRE, Kubernetes, Terraform, cloud (AWS preferred), experience with ML workload infrastructure a strong plus.
  • AI QE Engineer (Mid-level) × 2 | Hyderabad / Bengaluru | Full-time, Mid-level | AI Practice. You'll work within our AI Practice pods, contributing to client-facing AI evaluation engagements and building the tooling that makes them repeatable at scale. Responsibilities: design and execute AI model evaluation frameworks for client AI systems; write automated eval suites using QAVE's API and custom eval tooling; contribute to SLM-powered compliance testing and regulatory mapping; work directly with clients to understand use cases and translate to eval plans. You bring: 2–4 years QE or software engineering, Python proficiency, curiosity about AI systems, willingness to get deep in regulatory and domain context.
  • Solutions Engineer — AI Practice | Bengaluru | Full-time, Senior | GTM. You'll be the technical voice in our AI Practice sales motion — owning demos, RFP responses, proof-of-concepts, and the technical handoff to delivery. You're as comfortable presenting to a CISO as you are writing eval scripts. Responsibilities: own QAVE and CHEQ demo environments and customise for prospects; lead technical discovery calls and translate client requirements to platform capabilities; write compelling technical sections of proposals and RFP responses; run proof-of-concept engagements (2–4 week sprints) that convert to deals. You bring: 4+ years QE or AI engineering, strong communication, ability to demo live under pressure, experience in BFSI or regulated tech a plus.
  • Regulatory SME — AI Compliance (IRDAI/RBI/EU AI Act) | Hyderabad / Remote | Full-time, Senior | GTM. A rare role sitting at the intersection of regulatory compliance and AI engineering. You'll shape CHEQ's obligation library, advise clients on regulatory strategy, and be the face of Qapitol at regulatory and industry forums. Responsibilities: maintain and expand CHEQ's obligation library across IRDAI, RBI, EU AI Act, DORA, ISO 42001; advise clients on AI compliance strategy and examination preparation; write compliance-focused content, whitepapers, and response frameworks; represent Qapitol at IRDAI/RBI/IAMAI working groups and industry events. You bring: 6+ years in financial services compliance, legal, or regulatory technology. Deep knowledge of IRDAI or RBI frameworks. Interest in AI governance essential.
  • Product Manager — QAVE Platform | Hyderabad | Full-time, Senior | Product. You'll own the QAVE product roadmap — balancing the needs of free-tier users driving adoption with enterprise customers demanding Sovereign AI deployment and custom compliance frameworks. Responsibilities: own QAVE's product strategy, roadmap, and KPIs (MAU, activation, expansion revenue); conduct customer discovery with enterprises, startups, and compliance teams; write crisp PRDs and work closely with engineering to ship high-quality features; define and track eval quality metrics and iterate on the free-tier onboarding funnel. You bring: 4+ years PM at B2B SaaS, technical background (can read code and critique architecture), strong analytical skills, experience with AI/ML products a plus.
  • Delivery Manager — QE (BFSI) | Hyderabad / Bengaluru | Full-time, Senior | Delivery. You'll own delivery excellence for 3–5 large BFSI client accounts — managing QE squads, ensuring outcomes, navigating client relationships, and driving expansion. This is a senior client-facing leadership role. Responsibilities: P&L ownership for your client portfolio (₹2–8Cr ARR); hire, manage, and develop a delivery team of 15–30 QE practitioners; drive monthly governance with C-level stakeholders at client organisations; lead AI practice adoption within accounts — introduce QAVE, CHEQ where relevant. You bring: 8+ years QE delivery, experience managing large client accounts, BFSI domain knowledge, strong executive communication.
  • Senior SDET — Automation (Playwright / Selenium) | Hyderabad / Bengaluru | Full-time, Senior | Delivery. You'll work within an embedded QE squad at a fast-growing fintech client, leading automation strategy and building a maintainable, scalable test suite using modern tooling. Responsibilities: design and build UI automation with Playwright (TypeScript) and API automation (RestAssured/SuperTest); integrate test execution into GitHub Actions CI/CD pipeline; mentor junior SDETs and conduct code reviews; explore and pilot AI-assisted test generation using Nexus and Agent Fabric. You bring: 4+ years automation engineering, strong Playwright or Selenium, TypeScript/Java, API testing, CI/CD experience.
  • Performance Engineering Lead | Hyderabad | Full-time, Senior | Delivery. You'll lead performance engineering across multiple client accounts, owning strategy, execution, and analysis for load, stress, soak, and chaos testing programmes. Responsibilities: design performance test strategies for microservices and cloud-native architectures; execute load testing with k6, Gatling, or JMeter at scale (100K+ VU); root cause analysis and remediation guidance — not just 'here's the report'; develop performance testing practice collateral and train delivery teams. You bring: 6+ years performance engineering, strong with k6/Gatling, cloud monitoring (Datadog, NewRelic, Grafana), distributed systems understanding.
  • AI QE Consultant — Client Delivery | Bengaluru | Full-time, Mid–Senior | Delivery. A client-facing consulting role combining QE expertise with AI practice knowledge. You'll advise clients on their AI testing strategy, design evaluation frameworks, and help them build in-house AI QE capability. Responsibilities: lead AI QE maturity assessments and produce roadmaps for client AI testing practices; design bespoke evaluation frameworks using QAVE for client-specific AI use cases; train and upskill client QE teams on AI evaluation concepts and tooling; own deliverables, timelines, and client satisfaction for advisory engagements. You bring: 4–7 years QE or advisory, exposure to AI/ML systems, strong deck and document writing, ability to translate technical complexity for business audiences.

What Tuesday actually looks like here.

Not what's on the careers page — what's in Slack at 10am on a random weekday. Could this be your Tuesday? Real problems. Smart teammates. AI tools to accelerate everything. If this sounds like work you'd enjoy, we'd like to talk.

  • 09:15 — AI Eval team standup: Three SDETs and an ML engineer reviewing overnight QAVE results on a new LLM. One hallucination pattern nobody expected. Fifteen minutes of genuine detective work. They file a bug against the model — not the test.
  • 11:30 — CHEQ obligation review: A compliance engineer is translating three new IRDAI circular paragraphs into machine-checkable obligations. She's on a call with a lawyer at HDFC — live editing a compliance obligation in CHEQ's UI while they talk.
  • 14:00 — Agent Fabric sprint demo: The platform team demos an agentic regression runner that cut test suite time by 68%. The PM immediately asks to productise it. A senior engineer is already writing the RFC before the call ends.
  • 16:00 — UAE client onboarding: A delivery lead is onboarding a new GCC client from Dubai — walking through DIFC AI regulation mapping in CHEQ for the first time. The client's CTO asks if they can extend the pilot. They can.
  • 17:30 — Labs experiment debrief: The Labs team is wrapping up a two-week spike on real-time compliance validation — checking requirements against policy as they're written. Works. Writing it up for the product team. Might ship in Q3.

Don't see your role?

Send us an open application. We sometimes hire for roles before we list them. If you're exceptional at something in AI engineering, QE, or GTM — tell us about yourself.

  • Submit Open Application →

Application Process (Multi-step form)

Step 1 — Fit check: Which best describes your primary area of expertise? (Quality Engineering / SDET / Test Automation; AI Engineering / ML / LLM Development; DevOps / Platform / SRE; Compliance / Regulatory / GRC; Product Management; Sales / Pre-Sales / GTM; Other / Not listed). How familiar are you with AI evaluation concepts — things like hallucination detection, bias testing, LLM red-teaming, or IRDAI / EU AI Act compliance? (I work in this area — it's my day job; I've read about it and explored the tools; I'm actively upskilling in this area; Fairly new to this — but very interested). What's your notice period / earliest start date? (Immediate / Serving notice; Up to 30 days; 30–60 days; 60–90 days; More than 90 days). Helper text: Your answers help us match you to the right team and fast-track your application. There are no wrong answers. Step 2 — Details: First Name, Last Name, Email, Phone, Current Company, Years of Experience (0–2 / 2–4 / 4–7 / 7–10 / 10+ years), LinkedIn / GitHub / Portfolio URL, Resume/CV upload (PDF or DOCX, max 5MB), 'What excites you most about this role at Qapitol? (2–3 sentences)'. Step 3 — Apply: What happens next: We review every application within 3 business days. Shortlisted candidates get a 30-min call with a practice lead — no coding tests at this stage. Success: 'Application received! We'll review your application and a practice lead will reach out within 3 business days. No auto-rejection emails — if you don't hear, feel free to nudge us at [email protected]. While you wait — read our latest AI quality thinking or try QAVE free to see the platform you'd be building on.'

What a week looks like for a senior AI engineer at Qapitol

Not aspirational. This is a representative week drawn from our actual delivery and R&D rhythm.

  • Monday — Eval run review: Reviewing QAVE outputs from weekend pipeline runs, tagging failure modes, filing issues against model behaviours — not test scripts.
  • Tuesday — Client sprint: Pair programming with the client engineering team on LLM feature validation — bridging what the model does and what the product needs it to do.
  • Wednesday — Internal R&D: Labs session — working on a new eval methodology or red-teaming technique. Protected time, no client interruptions.
  • Thursday — Delivery review: Presenting an eval report to the client, their CISO, or governance committee. You own the narrative — engineering to boardroom.
  • Friday — Learning & craft: Team learning session, architecture review, or publishing to Qapitol Labs blog. We invest in craft — every week, not just quarterly.

We pay competitively. Here's what that means.

We're not going to list numbers on a page — because compensation is contextual. But we'll tell you exactly what our philosophy is, so there are no surprises. Quote: 'We'll share our bands at the first conversation. No games.'

  • Benchmarked against AI-native firms — We benchmark against top-tier BFSI tech and AI-native startups — not traditional IT services companies.
  • ESOPs for senior hires — ESOP participation available for Band 4 and above. We want the team to own a piece of what we're building.
  • Annual review with market adjustment — Not just CPI. We look at market movement and your individual growth. If the market moves, we move with it.
  • No bond agreements — No bond agreements. No notice period penalties beyond standard. We're confident enough in the work to not trap people.

Current openings (Always Hiring)

Qapitol is always looking for exceptional people in these areas. These are representative roles — we may have more open by the time you read this. Reach out. Don't see your role? We're always looking for exceptional people. Send us your CV →

  • Senior AI/ML Engineer | AI Engineering | Hyderabad / Remote | Full-time
  • LLM Evaluation Specialist | Qapitol Labs | Bengaluru / Remote | Full-time
  • AI Governance Analyst | CHEQ platform team | Mumbai / Remote | Full-time
  • Agentic QE Lead | Delivery | Hyderabad / Client sites | Full-time
  • AI Programme Manager | GCC practice | Hyderabad | Full-time

Ready to build AI quality engineering's future?

13 open roles across AI Engineering, Platform, GTM, and Delivery. Apply today.

  • See All Roles →
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