QA Automation Engineer Intern

AI Prof; Hyderabad; On-site; INR 279,000 - 335,000; Full time

Benefits offered by this job

Stipend: ₹25,000–₹30,000 / month

Full-time role after internship

Job summary

AI Prof is seeking a QA Automation Engineer Intern to design, build, and own automated test pipelines across a multi-layered healthcare AI stack. You will simulate end-to-end clinical workflows from patient intake to clinician dashboards and continuously explore AI testing tools to accelerate test-writing velocity.

You will work with FDEs and the AI Evaluation team to ensure test coverage reflects real hospital risks, while embedding quality gates into CI/CD pipelines for every deployment.

Qualifications

• Academic standing: final year student with no active backlogs and CGPA above 7.5.
• A portfolio of non-trivial automation projects demonstrating testing impact.
• Hands-on testing experience with test automation tools in real-world projects.
• Genuine enthusiasm for healthcare where software quality safeguards lives.

Responsibilities

• Design, build, and maintain automated test pipelines across web, mobile, REST/gRPC APIs, Voice AI, and LLM workflows.
• Create test suites simulating end-to-end clinical workflows from patient intake to clinician dashboards.
• Evaluate emerging AI testing tools, synthetic data utilities, and AI-assisted testing for speed and coverage.
• Integrate frameworks into CI/CD so checks run automatically on every PR/build.
• Test telephony/voice workflows and hospital data integrations (FHIR/HL7).
• Collaborate with Forward Deployed Engineers and AI Evaluation teams to mirror real-world risks.

Skills

Playwright

Cypress

Selenium

Appium

pytest

Postman

Education

CGPA 7.5+

Tools

GitHub Actions

GitLab CI

Job description

Our Healthcare Quality & Reliability team builds the automated testing backbone that protects every product across our platform spanning client web applications, mobile interfaces, backend APIs, Voice AI, LLM workflows, and live telephony integrations.This is patient-safety-critical software; a defect slipping into production is not just a minor bug ticket it is a direct risk to live hospital operations and clinical care. We do not rely on manual click testing or textbook QA checklists. We build resilient, automated machines that stress-test non-deterministic AI systems, catch edge-case failures before code touches a hospital network, and maintain zero-compromise reliability as our deployment frequency scales.

About the Role

As a QA Automation Engineer Intern, you will design, engineer, and own automated test pipelines across our multi-layered healthcare AI stack. You will build test suites simulating end-to-end clinical workflows from patient intake to clinician-facing dashboards to backend data synchronization.In addition to traditional test automation, you will be expected to continuously explore, evaluate, and integrate emerging AI developer tools, automated test-generation utilities, synthetic evaluation agents, and modern LLM grading frameworks. You will leverage these modern technologies directly to accelerate test-writing velocity, automate regression suites, and elevate overall quality-assurance efficiency.

What You'll Do

• Engineer Multi-Layered Test Automation: Design, build, and maintain automated test pipelines covering web, mobile, REST/gRPC APIs, Voice AI pipelines, and agentic LLM workflows end to end.
• Validate Non-Deterministic AI & Voice Systems: Build specialized evaluation frameworks for Voice AI and LLM capabilities testing multi-turn conversational flows, voice quality, latency, function/tool-call accuracy, and failure recovery under harsh audio conditions.
• Automate Patient-Safety Regression Suites: Construct comprehensive, automated regression tests so that every new deployment is validated against critical clinical paths before going live.
• Integrate Quality Gates into CI/CD: Embed automated test frameworks directly into continuous integration and deployment pipelines, ensuring quality checks execute automatically on every pull request and build.
• Simulate Complex Telephony & API Workflows: Build specialized mock tools to test telephony/voice scenarios (call routing, dropping audio, unexpected user interruptions, latency spikes) and validate complex hospital data integrations (FHIR/HL7 schemas).
• Leverage Cutting-Edge AI Tools for Efficiency: Research, adopt, and evaluate new AI testing tools, automated test-script generators, synthetic edge-case synthesizers, and AI-assisted log-analysis utilities to systematically improve test coverage and execution speed.
• Track Quality Metrics & Reduce Flakiness: Instrument test suites to monitor flakiness, coverage, and regression trends relentlessly optimizing frameworks to distinguish real production regressions from unstable tests.
• Partner with Field Teams: Work shoulder to shoulder with Forward Deployed Engineers (FDEs) and the AI Evaluation team to ensure test coverage mirrors real-world hospital operational risks.

What We're Looking For

Technical

• Automation Ecosystems : Hands-on project experience with modern automation frameworks Playwright, Cypress, Selenium (web), Appium (mobile), or pytest/Postman (API).
• AI Tooling & Automation Efficiency: Practical knowledge of modern AI coding assistants, automated test generators, or synthetic data tools to rapidly create edge-case test suites and streamline debugging workflows.
• CI/CD & Observability : Understanding of CI/CD integration (GitHub Actions, GitLab CI, or similar) and comfort reading system logs to trace failures through complex, distributed architectures.
• AI & API Testing Concepts: Basic understanding of validating REST APIs, asynchronous event streams, and adapting QA methodologies to non-deterministic LLM/Voice outputs.

Good to Have

• Telephony & Real-Time Audio Testing : Exposure to WebRTC, SIP protocols, or programmable voice APIs (Twilio, LiveKit) for verifying low-latency audio pipelines.
• Healthcare Compliance & Data Standards : Familiarity with HIPAA, SOC 2 compliance requirements, or healthcare data formats (FHIR, HL7).
• LLM Evaluation & Agent Testing : Hands-on experience with automated agentic eval harnesses (Ragas, DeepEval, Braintrust) or prompt-trajectory regression testing.
• Performance & Load Testing : Understanding of load and stress-testing tools (k6, Locust, JMeter) for validating high-concurrency API performance.

Mindset

• Obsessive Attention to Detail : You naturally look for the edge case that "should never happen" and build a test to catch it before it hits production.
• Skeptical by Default : You operate with a scientific mindset assuming code is broken until systematic automated tests prove otherwise.
• Extreme Ownership : You treat quality gaps as your personal problem to flag and fix, never assuming someone else will catch the error downstream.
• Clear Technical Communication : You translate complex test failures into precise, actionable bug reports that allow engineering teams to fix root causes rapidly.
• Bias to Action & Resourcefulness : You would rather build an automated test harness today than manually recheck the same flow tomorrow.

Qualifications

• Academic Standing : Final year student with no active backlogs and a CGPA above 7.5 (or equivalent proof of strong analytical capability).
• Demonstrated Track Record : A portfolio of non-trivial automation projects (GitHub repositories, custom test frameworks, hackathon builds, or open-source contributions) what you have actually engineered matters far more than formal credentials.
• Hands-On Testing Experience : Direct prior experience building or using test automation tools (personal projects, open-source work, or previous internships are valued equally).
• Domain Drive: Genuine enthusiasm for healthcare as an industry where software quality and reliability directly safeguard human lives.

Why This Role

Testing agentic AI, real-time Voice systems, and complex healthcare integrations is one of the most demanding applied QA challenges in software today. You won't be writing repetitive manual test scripts you will build the automated safety net that protects real hospitals. You will gain deep, rare expertise testing cutting-edge AI architectures under high-stakes, real-world deployment conditions.

What You'll Get

• High-Impact Stipend : ₹25,000 – ₹30,000 / month (scaled directly to skill depth, efficiency, and drive).
• FastTrack Career Growth: Top performers convert to a full-time role with a package of ₹6–10 LPA, based on impact and ownership shown during the internship.
• Own the Production Safety Net : Build the automated systems that catch failures before they ever reach a real hospital your code is our last line of defense.
• Test Advanced AI Stacks : Build highly sought-after skills testing multi-agent systems, WebRTC streaming, Voice AI, and healthcare APIs.
• Field-Tested Impact : Collaborate directly with FDEs to stress-test software against live hospital operational conditions.

Our Culture

If you view your time here as ordinary employment, this is not the right place for you. We are building the quality foundation for healthcare AI, requiring deep commitment, speed, and continuous technical rigor. From day one, you are an architect of our software reliability and engineering standards.

Our Non-Negotiables

• Uncompromising Honesty : Direct and candid communication, especially when identifying critical defects or safety vulnerabilities.
• Hard Work & Humility : High technical execution capacity paired with zero ego in problem solving debates.
• Impact for Humanity: Ensure every system tested tangibly protects patient safety and operational trust.
• Relentless Excellence : Setting high quality as the baseline and obsessing over the final 1% of detail.
• Extreme Ownership : Take total accountability. There is no "that is not my job" here.
• Bias to Action : Make informed decisions fast, execute fiercely, and adapt based on live system metrics.
• Solve Aggressively, Ask Fearlessly : Bring proposed fixes alongside problems, and raise technical blockers early to maintain momentum.
• Resourcefulness & Frugality : Embrace technical constraints; leverage modern AI tools to maximize test automation output and efficiency.
• Disagree Openly, Commit Fully : Debate quality strategies passionately, then align 100% behind the selected path.