Senior GenAI Quality Engineer and Solution Analyst

SAKSOFT PTE LIMITED; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SAKSOFT PTE LIMITED is seeking a Senior GenAI Quality Engineer and Solution Analyst in Singapore to lead end-to-end testing across UI, API, and GenAI-enabled workflows. The role focuses on designing robust test strategies for complex applications and ensuring reliable agentic interactions with non-deterministic GenAI outputs.

The candidate will validate responses, execute diverse test types, and drive quality by collaborating with product owners, engineers and GenAI specialists.

Qualifications

• : 5 to 8 years of experience in software quality engineering, test engineering or a similar hands on role covering complex applications.
• : Strong experience testing web user interfaces, backend services and REST APIs.
• : Hands on ability with API tools and automation frameworks such as Postman, REST Assured, pytest, Playwright, Cypress, Selenium or equivalent.
• : Working knowledge of Java, Python, JavaScript or TypeScript sufficient to build, review and troubleshoot test automation.
• : Strong test analysis skills, including requirements review, risk assessment, boundary analysis, negative testing and traceability.

Responsibilities

• : Define and execute end to end test strategies covering UI workflows, backend APIs, integrations and agentic interfaces.
• : Test conversational and agentic behaviour including multi turn context, tool selection, tool inputs and outputs, state transitions, retries, timeouts, handoffs, approvals and recovery from partial failure.
• : Validate GenAI responses for task completion, grounding, relevance, consistency, citation behaviour and safe failure, while recognising that outputs can be non deterministic.
• : Perform functional, integration, regression, exploratory, negative, resilience and basic performance testing across application layers.
• : Design API tests for contracts, authentication, authorisation, validation, error handling, idempotency, rate limits and downstream failures.
• : Test UI behaviour across browsers and realistic user journeys, including loading states, interrupted sessions, feedback capture, accessibility basics and clear error communication.
• : Create and maintain test data, reusable test scenarios and traceable evidence suitable for enterprise release governance.
• : Use logs, traces, request and response payloads and observability tools to isolate defects and distinguish application, model, data, integration and platform issues.
• : Automate the tests that materially reduce cycle time, manual effort or production risk, and keep unstable or low value scenarios out of the automation suite.
• : Communicate defects and quality risks clearly to engineers, product owners, GenAI specialists, security teams and business stakeholders.
• : Provide an evidence based release recommendation, including known limitations, residual risks and areas requiring monitoring.
• : Partner with product owners, business users, architects, engineers and GenAI specialists to define the problem, target user journeys and expected business outcomes.
• : Analyse proposed GenAI use cases and determine where deterministic application logic, retrieval, workflow orchestration, tool using agents or human approval should be used.
• : Translate business requirements into end to end solution flows, functional requirements, interface behaviors, decision rules, acceptance criteria and non functional requirements.
• : Map interactions across user interfaces, APIs, models, prompts, retrieval components, enterprise data sources, agent tools and downstream systems.
• : Analyse solution options and document tradeoffs relating to quality, complexity, cost, latency, security, data access, maintainability and operational risk.
• : Identify unclear ownership, missing controls, integration assumptions, failure scenarios and operational gaps before development begins.
• : Support the design of human approval, fallback, escalation and exception handling paths for agentic solutions.
• : Define measurable success criteria covering business outcomes, user experience, functional correctness, response quality, latency, reliability and safe failure.
• : Maintain traceability from business need through solution requirement, implementation, evaluation scenario and release evidence.
• : Facilitate structured design reviews and communicate findings using process flows, sequence diagrams, interface specifications, decision tables and concise solution documentation.

Skills

UI testing

API testing

GenAI testing

Risk-based testing

Observability

End-to-end testing

Test strategy

Stakeholder communication

Tools

Postman

REST Assured

pytest

Playwright

Cypress

Selenium

Job description

Experience : 6-9 Years

Role : Senior GenAI Quality Engineer and Solution Analyst

Key Skills:

• UI and API Quality Engineering
• Agentic and GenAI Application Testing
• Risk Based Test Automation and Observability

Responsibilities:

• Define and execute end to end test strategiescovering UI workflows, backend APIs, integrations and agentic interfaces.
• Test conversational and agentic behaviour including multi turn context, tool selection, tool inputs and outputs, state transitions, retries, timeouts, handoffs, approvals and recovery from partial failure.
• Validate GenAI responses for task completion, grounding, relevance, consistency, citation behaviour and safe failure, while recognising that outputs can be non deterministic.
• Perform functional, integration, regression, exploratory, negative, resilience and basic performance testing acrossapplication layers.
• Design API tests for contracts, authentication, authorisation, validation, error handling, idempotency, rate limits and downstream failures.
• Test UI behaviour across browsers and realistic user journeys, including loading states, interrupted sessions, feedback capture, accessibility basics and clear error communication.
• Create and maintain test data, reusable test scenarios and traceable evidence suitable for enterprise release governance.
• Use logs, traces, request and response payloads and observability tools to isolate defects and distinguish application, model, data, integration and platform issues.
• Automate the tests that materially reduce cycle time, manual effort or production risk, and keep unstable or low value scenarios out of the automation suite.
• Communicate defects and quality risks clearly to engineers, product owners, GenAI specialists, security teams and business stakeholders.
• Provide an evidence based release recommendation, including known limitations, residual risks and areas requiring monitoring.
• Partner with product owners, business users, architects, engineers and GenAI specialists to define the problem, target user journeys and expected business outcomes.
• Analyse proposed GenAI use cases and determine where deterministic application logic, retrieval, workflow orchestration, tool using agents or human approval should be used.
• Translate business requirements into end to end solution flows, functional requirements, interface behaviors, decision rules, acceptance criteria and non functional requirements.
• Map interactions across user interfaces, APIs, models, prompts, retrieval components, enterprise data sources, agent tools and downstream systems.
• Analyse solution options and document tradeoffs relating to quality, complexity, cost, latency, security, data access, maintainability and operational risk.
• Identify unclear ownership, missing controls, integration assumptions, failure scenarios and operational gaps before development begins.
• Support the design of human approval, fallback, escalation and exception handling paths for agentic solutions.
• Define measurable success criteria covering business outcomes, user experience, functional correctness, response quality, latency, reliability and safe failure.
• Maintain traceability from business need through solution requirement, implementation, evaluation scenario and release evidence.
• Facilitate structured design reviews and communicate findings using process flows, sequence diagrams, interface specifications, decision tables and concise solution documentation.

Requirements:

Core Requirements

• 5 to 8 years of experience in software quality engineering, test engineering or a similar hands on role covering complex applications.
• Strong experience testing web user interfaces, backend services and REST APIs.
• Hands on ability with API tools and automation frameworks such as Postman, REST Assured, pytest, Playwright, Cypress, Selenium or equivalent.
• Working knowledge of Java, Python, JavaScriptor TypeScript sufficient to build, review and troubleshoot test automation.
• Strong test analysis skills, including requirements review, risk assessment, boundary analysis, negative testing and traceability.
• Experience validating distributed systems and integrations, including asynchronous processing, queues, batch jobs and downstream dependencies.
• Ability to inspect logs, traces, networkcalls, payloads and database records to identify the actual failure point.
• Experience with Git, pull requests, CI/CDpipelines, test reporting and defect management tools.
• Understanding of security and privacy testing fundamentals, including access control, sensitive data handling, input validation and auditability.
• Strong stakeholder communication and the confidence to challenge weak designs, vague expected outcomes and premature release decisions.
• Ability to work in a fast moving environment where requirements and GenAI behaviour evolve.

Solution analysis and design expectations

• Experience analysing complex applications