Hyderabad · Senior
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Presales Solution Architect, Quality Engineering (AI and GenAI)
Digital Engineering (DE-QE) | Hyderabad, India | Work from office
OSI Digital is seeking an experienced Presales Solution Consultant for its Quality Engineering practice. This person owns presales for QE and drives QE accelerators as a product line: turning customer testing problems into scoped, defensible solutions and commercial proposals, and building reusable QE assets that OSI can sell repeatedly.
The role is customer facing and solution led, not a pure delivery seat. It suits someone with real QE delivery depth, strong research instincts, and genuine hands-on AI and GenAI ability, who wants to shape and sell solutions while staying technically credible.
Key Responsibilities
Own presales for the QE practice: qualify opportunities, run discovery calls, and scope QE solutions covering test strategy, test automation, performance, and security testing.
Build effort estimates, proposals, solution decks, and responses to RFP and RFI documents, and defend the assumptions with customer stakeholders.
Prepare and run tailored demos and proofs of concept, including AI assisted testing demos.
Position and sell OSI accelerators into QE opportunities, showing where each reduces testing effort, cost, or risk.
Identify, design, and drive net-new QE accelerators: reusable automation frameworks, AI assisted testing assets, and repeatable solution packages the practice can sell more than once.
Own the go-to-market for QE accelerators: the pitch narrative, the demo, the reference architecture, and the packaging story.
Design and demonstrate Gen AI assisted testing workflows: test case generation from requirements, test data synthesis, and automated test script drafting.
Evaluate and honestly position AI features in testing tools, for example self-healing locators, visual validation, and risk-based test selection.
Prototype LLM and retrieval-based aids for QE, such as a knowledge assistant over test documentation or GenAI support for defect triage.
Research the QE tooling and vendor landscape and each prospect before engagement, and separate real capability from vendor marketing.
Bridge the sold solution and the delivery team and contribute hands-on to early delivery on strategic accounts, so the approach is proven in practice.
Support architecture and code reviews for QE automation and drive AI, GenAI adoption across the QE team.
Produce solution documentation, reusable assets, and enablement material.
Required Skills and Experience
Core Experience
5 to 9 years of overall QA and QE experience, with at least 5 years hands-on in test automation.
2 or more years of practical, hands-on use of LLMs or GenAI in real work, not just awareness.
Prior presales, solution consulting, or strong customer facing delivery exposure.
QE and Automation Skills
Strong with automation frameworks such as Selenium, Playwright, Cypress, and RestAssured.
API and UI automation, regression, and in-sprint testing.
Test integration in CI/CD pipelines and Git-based workflows.
Performance testing (JMeter, k6, or NeoLoad) is an advantage.
Presales and Accelerator Skills
Scoping and estimating technical engagements and defending the assumptions.
Building proposals and presenting confidently to customer stakeholders.
Track record of building reusable frameworks or assets that can be productized, not just one-off delivery.
AI and GenAI Skills
Practical use of LLMs in real work, with the ability to check and validate generated output.
Prompt design and retrieval (RAG) at a working level.
Python or scripting for AI prototypes.
Cloud and Ecosystem
Understand at least one cloud platform (Azure, AWS, or GCP).
Experience with Containerized test environments is an advantage.
Nice to Have
Experience taking an internal accelerator or product to market, including pricing or packaging.
Exposure to enterprise ERP or regulated industry testing.
Security testing.
Experience with AI augmented testing tools and vector databases.
We are not looking for someone who
Is not willing to work from the office.
Has never worked directly with customers or in a client facing role.
Has only manual testing experience with no hands-on automation.
Treats AI and GenAI as buzzwords, with no real hands-on usage.
Wants a pure delivery seat with no presales, solutioning, or customer interaction.
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