RPA-GenAI Trust and Assurance Consultant

Job Description:

• Step into a role where you help teams build Generative AI solutions that are not only powerful but also trustworthy safe and testable
• As part of a collaborative consulting environment you ll work closely with product engineering and risk stakeholders to design practical assurance approaches for LLM powered systems balancing innovation with reliability
• You ll contribute to real world AI validation efforts from defining test strategies and evaluation metrics to executing red teaming exercises and documenting outcomes that leadership can act on
• If you enjoy combining structured testing discipline with the fast evolving world of GenAI this is a chance to shape how AI quality safety and responsibility are measured and improved while learning alongside motivated teams solving meaningful problems

Key Responsibilities:

• Define and execute testing strategies for Generative AI LLM systems covering functional non functional and safety focused validation
• Design evaluation frameworks and test suites using tools such as DeepEval to measure quality robustness and consistency of model outputs
• Plan and conduct red teaming exercises to identify vulnerabilities e
• g
• prompt injection jailbreaks harmful content data leakage and recommend mitigations
• Establish Responsible AI assurance checks aligned to fairness transparency privacy and safety expectations
• Create clear test plans evidence dashboards and reports that communicate risks findings and remediation priorities to stakeholders
• Collaborate with engineering and product teams to integrate AI testing into delivery pipelines and improve release readiness criteria
• Support incident triage and root cause analysis for model behavior issues regressions and evaluation drift across versions

Technical Requirements:

• BTech BE or equivalent technical degree
• 3 9 years of experience in testing quality engineering with hands on exposure to Generative AI or LLM testing initiatives
• Working knowledge of AI testing concepts including test design evaluation metrics and result interpretation for LLM outputs
• Experience contributing to structured documentation such as test plans test evidence and defect risk reporting

Additional Responsibilities:

• Proven experience executing red teaming for LLM applications and translating findings into actionable controls and mitigations
• Practical experience implementing Responsible AI practices and assurance workflows across the AI lifecycle
• Strong understanding of LLM failure modes hallucinations toxicity bias prompt sensitivity and methods to test and reduce them
• Experience building automated evaluation pipelines and regression suites for LLM systems using DeepEval or similar frameworks
• Consulting experience stakeholder management requirement discovery and delivering clear outcomes under ambiguity

Preferred Skills:

Technology->Machine Learning->Generative AI,Technology->Generative AI->Prompt Engineering,Technology->Machine Learning->Responsible AI,Technology->Agentic AI->Agent Engineering,Technology->AI Engineering->LLMOps,Technology->Testing Technologyes->Test Automation Technology->Testing,Technology->Data Science->Machine Learning