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orbitshift.ai

QA Engineer

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  • Posted 22 hours ago
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Job Description

About OrbitShift

At OrbitShift, we are building the world's first AI-native Sales Operating System, trusted by

enterprise teams to accelerate their GTM motion. Our multi-agent AI system enables actionable

account insights, RFP response generation, targeted nudges, and sales content. Backed by

Peak XV (formerly Sequoia Capital), Stellaris Venture Partners, and other marquee investors,

we are a fast-growing, 3-year-old startup with a team from Amazon, McKinsey, IIT, and

Stanford.

Quality is not a phase at OrbitShift — it is a mindset embedded across the engineering culture.

We are looking for a QA Engineer who takes genuine ownership of product reliability and brings

both the discipline of structured manual testing and the leverage of well-built automation to keep

our platform enterprise-grade as it scales.

Role Overview

As a QA Engineer at OrbitShift, you will be the last line of defence before software reaches

enterprise customers — and an early line of offence in catching problems before they are even

built. You will work closely with product managers, engineers, and designers across the full

development lifecycle: reviewing requirements for testability, designing test strategies, executing

manual test cases, and building automation suites that give the team confidence to ship fast

without breaking things.

This role demands someone who is meticulous without being slow, who can think adversarially

about product behaviour, and who understands that testing AI-powered systems introduces a

layer of non-determinism that standard QA playbooks do not fully cover. You will help define

what quality means for an AI product, not just validate it.

Key Responsibilities

• Test Strategy & Planning: Review PRDs, user stories, and technical designs to identify

testability gaps early. Define test plans, test coverage matrices, and risk-based

prioritisation for each release.

• Manual Testing: Design and execute thorough manual test cases for functional,

regression, exploratory, edge case, and UX validation across web and API surfaces.

Document findings with clarity and reproducibility.

• Automation Engineering: Build, maintain, and extend automated test suites for functional

regression, API contracts, and end-to-end user journeys. Integrate tests into CI/CD

pipelines so quality gates are automated, not manual.

• AI Feature Testing: Develop testing strategies for AI-powered features — including output

consistency checks, prompt regression testing, hallucination detection, and edge case

cataloguing. Work with ML engineers to define acceptable quality thresholds for model

outputs.

• Bug Lifecycle Ownership: File clear, well-evidenced bug reports with steps to reproduce,

expected vs. actual behaviour, severity classification, and supporting artefacts. Track

bugs through to closure and verify fixes rigorously.

• Performance & Load Testing: Design and run performance tests to validate system

behaviour under realistic and peak enterprise load conditions. Surface bottlenecks before

they become customer incidents.

• Release Readiness: Own the release sign-off process — coordinate with engineering and

product to define go/no-go criteria, maintain a release checklist, and communicate quality

status clearly to stakeholders.

• Process Improvement: Continuously evaluate and improve QA processes, tooling, and

coverage. Identify patterns in defects and drive root cause elimination upstream.

What We're Looking For

• 3–6 years of QA experience across manual and automation testing, ideally in a B2B SaaS

or enterprise software environment.

• Proven track record of owning test strategy and execution for complex, multi-component

products in an agile delivery environment.

• Experience testing both frontend web applications and backend APIs — comfortable

context-switching between UI flows and API contracts within the same sprint.

Manual Testing Skills

• Strong command of test case design techniques: equivalence partitioning, boundary value

analysis, decision tables, state transition testing, and exploratory testing heuristics.

• Experience writing detailed, reproducible test cases and maintaining them across evolving

product versions.

• Sharp eye for UX issues, accessibility gaps, and edge cases that automated tests are

unlikely to catch.

• Familiarity with API testing using tools such as Postman, Insomnia, or similar — ability to

validate request/response contracts, authentication flows, and error handling

independently.

Automation Skills

• Hands-on experience building and maintaining automated test suites using frameworks

such as Selenium, Playwright, Cypress, or similar for UI automation.

• Proficiency with at least one scripting or programming language — Python or JavaScript

preferred — to write and debug test scripts without engineering support.

• Experience integrating automated tests into CI/CD pipelines (GitHub Actions, Jenkins,

GitLab CI, or equivalent).

• Familiarity with API automation using REST Assured, Pytest, or similar; experience

validating data-heavy workflows end-to-end.

• Understanding of test data management, environment isolation, and flaky test diagnosis

and remediation.

AI Product Testing

• Exposure to or curiosity about testing non-deterministic AI systems — understanding that

the same input can produce varying outputs and that quality thresholds for AI features

must be defined probabilistically.

• Familiarity with LLM output evaluation concepts (correctness, groundedness, relevance,

tone) is a strong plus.

Nice to Have

• Experience with performance and load testing tools such as k6, JMeter, or Locust.

• Exposure to security testing basics — OWASP Top 10 awareness, input validation

checks, and authentication testing.

• Familiarity with observability and monitoring tools (Datadog, Sentry, or similar) to connect

QA findings with production signals.

• ISTQB Foundation certification or equivalent formal QA training.

You Will Thrive Here If

• You think of quality as a product responsibility, not a gating function. You are proactive,

not reactive.

• You are comfortable operating with autonomy — you do not need to be assigned every

test case; you figure out what needs to be tested and do it.

• You can hold your ground in a room of engineers. You file clear, well-evidenced bugs and

follow through until they are resolved.

• You get genuinely curious when something behaves unexpectedly — not frustrated. You

dig until you understand why.

• You care about the end user. Every bug you catch is a bad experience prevented for an

enterprise customer.

Why Join Us

• Meaningful ownership of quality in a fast-scaling AI product used by enterprise sales

teams globally.

• Work alongside engineers from Amazon, IIT, and Stanford in a team that takes quality

seriously as a cultural value.

• Exposure to cutting-edge AI system testing challenges that are genuinely new — no

established playbook, just clear thinking and good engineering.

• Competitive compensation, growth into senior QA or SDET roles, and the satisfaction of

shipping software that actually works.

*OrbitShift is an equal-opportunity employer. Candidates will not be discriminated against based on race, ethnicity, color, religion, caste, sex, gender identity, sexual orientation, national origin, veteran, or disability status.

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Job ID: 147184393

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