Senior AI Engineer in Test

TekWissen LLC; Lakshadweep; Hybrid; INR 8,671,000 - 12,524,000; Full time

Job summary

TekWissen Group is seeking a hands-on Senior AI Engineer in Test to lead AI-enabled testing across the Software Testing Lifecycle. You will evaluate AI models and testing pipelines, build technical POCs, and compare tools and platforms to drive AI quality engineering across client delivery teams.

This hybrid, full-time role focuses on performance, security, and observability in AI testing. The role requires strong Python skills, experience with AI platforms, and the ability to communicate

Qualifications

• Hands-on experience in quality engineering and AI-enabled testing practices.
• Experience defining evaluation metrics, scoring frameworks, and thresholds for AI solutions.
• Proficiency in Python or similar for prototypes, automation, and accelerators.
• Ability to build POCs and evaluate testing tools and frameworks with evidence-based recommendations.
• Familiarity with Copilot Studio, Azure AI Foundry, Pega AI, Snowflake Cortex AI or similar platforms.
• Understanding of AI-specific risks such as prompt injection and associated mitigations.
• Strong analytical, problem-solving, and technical communication skills.

Responsibilities

• Define and validate AI-enabled testing strategies across the Software Testing Lifecycle (STLC).
• Design and implement AI model evaluation frameworks, including quality metrics, scoring, thresholds, drift monitoring, and post-production validation.
• Build and lead technical POCs to assess AI testing approaches across platforms like Copilot Studio, Azure AI Foundry, Pega AI, Snowflake Cortex AI.
• Evaluate and compare native platform capabilities, third-party tools, and open-source frameworks with evidence-based recommendations.
• Establish AI quality standards, evaluation criteria, and Definition of Done for AI-enabled solutions.
• Develop AI-assisted approaches for specification analysis, test generation, data creation, coverage assessment, and regression optimization.
• Create POCs for AI-driven test design, automation, defect triage, root cause analysis, and quality engineering transformation.
• Validate non-functional and AI-specific testing practices including performance, security, resilience, observability, and prompt injection testing.
• Document findings, reusable patterns, and recommendations to support AI testing strategy across delivery teams.

Skills

AI testing

Quality engineering

Test automation

Model evaluation

Prompt injection testing

Stakeholder management

Python

Tools

Copilot Studio

Azure AI Foundry

Pega AI

Snowflake Cortex AI

Job description

Overview:

TekWissen is a global workforce management provider throughout India and many other countries in the world. The below job opportunity is to one of our clients who is a part of a trusted global innovator of IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, IT modernization and managed services. This client enables us to move confidently into the digital future. This client committed to Long Term success and combine global reach with local client attention to serve them in over 50 Countries.

Position: Senior AI Engineer in Test

Location: Any Clients Location

Work Type: Hybrid

Job Type: Full Time

• Seeking a hands-on Senior AI Engineer in Test to define and validate AI-enabled testing strategies across the STLC, with a focus on AI solution evaluation, model assessment, tooling evaluation, and technical POC delivery.
• The role will drive validation of AI testing approaches across platforms such as Copilot Studio, Azure AI Foundry, Pega AI, and Snowflake Cortex AI, supporting the adoption of AI-driven quality engineering practices through evidence-based recommendations and reusable solutions.

Key Responsibilities:

• Define and validate AI-enabled testing strategies across the Software Testing Lifecycle (STLC).
• Design and implement AI model evaluation frameworks, including quality metrics, scoring mechanisms, acceptance thresholds, drift monitoring, and post-production validation.
• Build and lead technical POCs to assess AI testing approaches, tools, and frameworks across platforms such as Copilot Studio, Azure AI Foundry, Pega AI, and Snowflake Cortex AI.
• Evaluate and compare native platform capabilities, third-party tools, and open-source frameworks, providing evidence-based recommendations.
• Establish AI quality standards, evaluation criteria, and Definition of Done requirements for AI-enabled solutions.
• Develop and validate AI-assisted approaches for specification analysis, test generation, test data creation, coverage assessment, and regression optimization.
• Build POCs for AI-driven test design, automation, defect triage, root cause analysis, and quality engineering transformation initiatives.
• Validate non-functional and AI-specific testing practices, including performance, security, resilience, observability, and prompt injection testing.
• Document findings, reusable patterns, and recommendations to support AI testing strategy and adoption across delivery teams.

Skills Experience:

• Strong experience in Quality Engineering, Software Testing, and AI-enabled testing practices.
• Solid understanding of AI solution testing, model evaluation, prompt evaluation, output quality assessment, and AI risk validation.
• Experience defining evaluation metrics, scoring frameworks, quality thresholds, and monitoring approaches for AI solutions.
• Hands-on expertise in developing technical prototypes, POCs, test automation solutions, and engineering accelerators using Python or similar technologies.
• Knowledge of AI-assisted test generation, specification-driven testing, regression optimization, and test automation.
• Experience evaluating testing tools and frameworks and producing objective, evidence-based recommendations.
• Familiarity with Copilot Studio, Azure AI Foundry, Pega AI, Snowflake Cortex AI, or similar AI platforms is highly desirable.
• Understanding of APIs, integrations, automation frameworks, and modern software delivery practices.
• Knowledge of performance, security, resilience, observability, and AI-specific security risks such as prompt injection.
• Strong analytical, problem-solving, stakeholder management, and technical communication skills.

TekWissen Group is an equal opportunity employer supporting workforce diversity