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Key Responsibilities
AI Assurance Architecture
* Architect platforms and frameworks for AI assurance, evaluation, and benchmarking
* Design systems for LLM, agent, and RAG evaluation across functional, non functional, and risk dimensions
* Define architectural patterns for Responsible AI, bias detection, explainability, and safety validation
* Build reusable assurance components supporting Business Assurance, Risk Assurance, and Reliability
Security, Reliability & Governance
* Architect AI testing and validation for security, privacy, prompt injection, and adversarial robustness
* Integrate red teaming, threat simulation, and chaos style validation for AI systems
* Define governance mechanisms for model usage, auditability, traceability, and compliance
* Ensure AI systems meet enterprise standards for resilience, fault tolerance, and observability
Platform & Engineering Enablement
* Design AI assurance platforms supporting automated test execution, reporting, and insights
* Enable integration with CI/CD pipelines to enforce AI quality gates
* Collaborate with QE engineering teams to embed AI assurance into the SDLC
* Mentor teams on AI risk identification and mitigation from an engineering perspective
Core Platforms, Frameworks & Tooling
* LLM and AI evaluation frameworks (PromptFoo, DeepEval, custom LLM evaluation harnesses)
* Prompt, RAG, and agent validation tooling (prompt testing frameworks, retrieval accuracy validators, agent workflow evaluators)
* Responsible AI and model risk tooling (Fairlearn, SHAP, Explainable AI libraries, toxicity and bias scanners)
* Security and adversarial testing tools for AI systems (PyRIT, Garak)
* AI red teaming and threat simulation frameworks (automated red team scripts, adversarial test suites for LLMs and agents)
* AI assurance automation and QE frameworks (Galileo)
* Observability for AI behavior and drift (Langfuse, Arize, Evidently, custom telemetry dashboards)
Client Orientation & Leadership
* Partner with product and engineering teams to identify AI Assurance opportunities and shape roadmaps
* Support client workshops, RFPs, and solution presentations
* Mentor engineers on AI/ML/Gen AI best practices and emerging technologies
* Translate complex AI concepts into business-friendly narratives
Must Have Qualifications
* 13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership
* Hands on expertise in AI/ML systems, LLM evaluation, and assurance frameworks
* Experience with AI red teaming, model risk management, or AI audit tooling
* Strong understanding of Responsible AI, AI risks, and governance principles
* Experience with security testing, adversarial testing, and reliability engineering
* Proficiency in Python, automation frameworks, and cloud platforms
Good to Have Skills
* Knowledge of regulatory or compliance considerations for AI systems
* Exposure to performance engineering, chaos engineering, or resilience testing for AI
* Contributions to internal platforms, frameworks, or standards
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