Agentic AI Frontier Engineer - Associate Director - 68938091

About The Role As an Agentic AI Frontier Engineer, you’ll lead the end-to-end architecture, design, and engineering of Agentic and Generative AI solutions for enterprise clients - turning complex business problems into scalable, secure, and responsible AI architecture built on LLMs, multi-agent systems, orchestration frameworks, and cloud-native platforms.

This high-visibility role sits at the center of Cognizant’s three-vector AI strategy: unlocking productivity, scaling AI adoption from pilots to enterprise-wide impact, and leading agent-led transformation. You’ll help shape how large enterprises move beyond experimentation to build, deploy, and govern intelligent systems at scale.

In this role, you’ll partner with business stakeholders, product owners, data scientists, engineers, and security teams to embed autonomous decision-making, human-in-the-loop controls, and Responsible AI principles across the solution lifecycle.

In This Role, You Will Agentic & Gen AI Frontier Engineers

• Architect multi-agent systems capable of autonomous task planning, execution, reflection, and escalation within defined harnesses and guardrails
• Design end-to-end Agentic & Gen AI architectures, including LLM selection, agent orchestration, memory, tools, and human oversight mechanisms
• Define architectures covering data ingestion, vector stores, prompt engineering, retrieval-augmented generation (RAG), agent workflows, APIs, and integration layers

Responsible & Ethical AI

• Embed Responsible AI principles including fairness, explainability, transparency, human oversight, blast radius, and kill-switch mechanisms
• Ensure compliance with AI governance standards, enterprise security policies, and regulatory frameworks
• Guide teams on agent behaviour constraints, risk mitigation, and outcome monitoring

Delivery & Stakeholder Engagement

• Translate business use cases into AI solution blueprints, reference architectures, and implementation roadmaps
• Support pre-sales, RFPs, solutioning, and deal credentialization by articulating Agentic AI value propositions
• Provide technical leadership to delivery teams across PoCs, pilots, and production deployments

Thought Leadership & Innovation

• Stay current with Generative AI, Agentic AI frameworks, LLM advancements, and industry trends
• Contribute to internal accelerators, reusable assets, and best practices
• Mentor architects and engineering teams on GenAI and agent-based system design

Work model We strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a remote position open to qualified applicants in the United States. Regardless of your working arrangement, we support a healthy work‑life balance through our wellbeing programs.

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

• 10+ years of experience in enterprise architecture, frontier engineering, AI engineering, or related technology leadership roles, with recent focus on Generative AI and Agentic AI.
• Hands-on knowledge of large language models, prompt engineering, retrieval-augmented generation, vector databases, agentic workflows, and agent orchestration frameworks.
• Experience designing AI, machine learning, or GenAI systems on hyperscaler platforms such as Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
• Strong understanding of API-driven architectures, microservices, event-driven systems, cloud-native platforms, containers, orchestration, MLOps, and LLMOps.
• Ability to communicate complex technical concepts clearly to business, technical, and executive audiences in client-facing or consulting environments.

These will help you stand out

• Master’s degree or Doctor of Philosophy degree in Computer Science, Engineering, or a related STEM field.
• Evidence of technical thought leadership, such as patents, technical publications, professional portfolio, peer recognition, or similar contributions.
• Experience with agentic AI governance frameworks, autonomous system controls, responsible AI practices, and outcome monitoring.
• Exposure to industry-specific Generative AI use cases across communications, media, technology, banking, financial services, healthcar…