DevOps Architect - 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 stakeholders These will help you stand out

Hands\-on experience conducting red\-team assessments on production AI systems and remediating critical vulnerabilities

Experience creating audit\-ready AI governance and compliance documentation for external or regulatory review

Ability to influence AI system design decisions by balancing technical feasibility with regulatory and risk considerations

Experience integrating fairness, safety evaluation, and monitoring pipelines into CI/CD workflows

Exposure to enterprise AI tooling such as NeMo Guardrails, Giskard, Arize, LangChain/LangGraph, or similar ecosystems

We’re excited to meet people who share our mission and can make an impact in a variety of ways. Don’t hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting perspectives to this role.