AI Risk Engineer Senior Associate 1

We are the leading provider of professional services to the middle market globally, our purpose is to instill confidence in a world of change, empowering our clients and people to realize their full potential.

Our exceptional people are the key to our unrivaled, inclusive culture and talent experience and our ability to be compelling to our clients.

You’ll find an environment that inspires and empowers you to thrive both personally and professionally.

There’s no one like you and that’s why there’s nowhere like RSM.

Position Summary We are seeking a technically strong and analytically minded AI Risk Engineer to join our Technology Risk Consulting team.

This role is designed for professionals with a solid academic foundation in Artificial Intelligence, Machine Learning, Data Science, Computer Science, or related technical disciplines, combined with hands-on experience supporting AI-enabled products, platforms, or enterprise AI initiatives.

The ideal candidate will have demonstrable experience working with global technology organizations or multinational enterprises and will be comfortable collaborating across cross-functional, geographically distributed teams.

The role combines technical AI knowledge with risk and advisory thinking to help organizations adopt AI responsibly while managing governance, security, privacy, model performance, compliance, and responsible AI risks.

Key Responsibilities • Perform AI risk, AI governance, responsible AI, and AI assurance assessments across enterprise environments.

•Evaluate generative AI solutions, machine learning systems, AI agents, AI platforms, and third-party AI services for operational, security, privacy, regulatory, and ethical risks.

•Assess AI lifecycle processes, including data sourcing, model development, testing, validation, deployment, monitoring, change management, and retirement.

•Review controls related to bias, fairness, explainability, transparency, accountability, human oversight, model performance, security, and privacy.

•Analyze AI architectures, workflows, and technical implementations to identify risk exposures and practical mitigation strategies.

•Support enterprise AI inventory, use-case classification, risk assessment, approval, monitoring, and governance initiatives.

•Partner with Engineering, Product, Cybersecurity, Legal, Privacy, Compliance, Data, Risk, and business teams to evaluate AI risks and controls.

•Participate in client workshops and stakeholder interviews, translating technical AI concepts into clear business and risk implications.

•Prepare client-facing reports, risk assessments, executive summaries, and practical advisory recommendations.

•Contribute to AI risk methodologies, assessment accelerators, thought leadership, and global engagements delivered through onshore/offshore operating models.

Required Qualifications • Bachelor's or master's degree in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Software Engineering, Applied Mathematics, Computational Statistics, Data Analytics, or a closely related technical discipline.

4+ years of experience across AI, machine learning, data science, AI engineering, MLOps, AI platform engineering, Trust & Safety, product risk, technology risk, cybersecurity, model risk management, data governance, or related technology disciplines.

•Demonstrable experience developing, supporting, evaluating, monitoring, governing, or assessing AI-enabled products, machine learning solutions, or generative AI use cases in production environments.

•Strong understanding of generative AI, large language models, AI agents, retrieval-augmented generation, model evaluation, AI lifecycle management, and responsible AI principles.

Working knowledge of AI risks including bias, fairness, explainability, privacy, security, robustness, model drift, human oversight, and third-party dependencies.

•Experience working with global firms in cross-functional and geographically distributed teams, including onshore/offshore delivery models.

•Strong written and verbal communication skills, with the ability to explain technical concepts to technical, business, and executive stakeholders.

•Demonstrated analytical, problem-solving, consultative, documentation, and stakeholder management skills.

Preferred Qualifications • Experience working for global technology companies, digital-first organizations, cloud providers, hyperscalers, AI product organizations, or large multinational enterprises.

•Experience supporting AI solutions at scale within production environments.

•Exposure to Microsoft Copilot, Azure AI, OpenAI, Anthropic, Google Vertex AI, AWS Bedrock, Databricks AI, Hugging Face, or similar enterprise AI technologies.

Familiarity with NIST AI RMF, ISO/IEC 42001, responsible AI frameworks, AI Trust & Safety, AI governance, or AI assurance practices.

•Experience supporting AI governance programs, AI assurance reviews, AI safety assessments, model evaluations, third-party AI risk reviews, or model risk initiatives.

•AI or machine learning certification such as AIIA, AIGP, ISO/IEC 42001 Lead Implementer or Auditor, Microsoft Azure AI Engineer Associate, AWS Machine Learning, Google Professional Machine Learning Engineer, or equivalent.

Working knowledge of AWS, Azure, or GCP and cloud-native AI services; exposure to cloud governance, IAM, cloud security, DevSecOps, Infrastructure as Code, or cloud resilience is an advantage.

•Prior experience within a Big 4, leading consulting organization, global technology company, or product engineering environment.

Success Profile • Strong AI and machine learning fundamentals supported by formal education and practical experience.

•Comfort navigating ambiguity in a rapidly evolving AI and regulatory environment.

•Ability to apply risk-based judgment and develop practical, business-focused solutions.

•Confidence working with engineering teams, business stakeholders, and executive audiences.

•Ability to thrive in cli