Responsible AI Engineer

Responsible AI Engineer

About the role

As a Responsible AI Engineer, you will make an impact by engineering the trust, safety, and governance layer for agentic AI systems deployed at enterprise scale. You will be a valued member of the AI Market Unit (FDE Pod) and work collaboratively with AI engineers, architects, risk teams, and client stakeholders to ensure every AI solution is safe, compliant, and production-ready.

In this role, you will:

• Design and implement runtime guardrails and safety architectures for LLM and agentic AI systems, including input/output controls, prompt injection detection, and policy enforcement mechanisms
• Lead red-teaming and adversarial testing initiatives to identify vulnerabilities such as jailbreaks, prompt injections, and trust boundary violations before production deployment
• Build and operationalize AI governance and compliance frameworks, translating regulations (e.g., EU AI Act, NIST AI RMF) into enforceable engineering controls
• Develop and deploy fairness, bias, and model evaluation pipelines, including hallucination detection, groundedness validation, and subgroup performance analysis
• Establish observability and auditability for AI systems through structured logging, audit trails, governance metrics, and incident response processes

Work model

At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role's business requirements, this is an onsite position requiring 5 days a week in a Cognizant office in Chennai, Bangalore, or Hyderabad.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• Experience in software engineering or ML engineering, with hands-on exposure to AI safety, governance, or trust engineering
• Proven experience building and deploying LLM or agentic AI systems in enterprise or regulated environments
• Strong expertise in at least two of the following: guardrails engineering, red teaming, bias/fairness evaluation, AI regulatory compliance
• Working knowledge of AI regulatory frameworks such as EU AI Act, NIST AI RMF, ISO/IEC 42001, or sector-specific compliance standards
• Strong Python programming skills, with experience building evaluation pipelines, observability systems, or AI governance tooling
• Ability to collaborate with security, legal, and risk stakeholders, translating technical AI risks into actionable insights for business leaders
• Excellent communication and executive-level presentation skills, with experience presenting to senior client stakeholder