Forward Deployed AI Engineer – Enterprise AI Architecture & Responsible AI

Cognizant is seeking a senior Forward Deployed AI Engineer to architect, build, and operationalize enterprise-scale AI systems for client transformation programs. The role combines hands-on AI engineering with enterprise architecture, responsible AI governance, and technical advisory, while supporting production adoption and capability transfer to client teams.

Responsibilities:

• Design and deliver AI-native enterprise architectures spanning applications, data platforms, business processes, and cloud environments
• Build production-grade Generative AI, RAG, and agentic AI solutions, taking ownership from architecture and prototyping through deployment and operation
• Define human-agent capability matrices, operating models, escalation paths, and human-in-the-loop controls for enterprise workflows
• Architect context pipelines, knowledge orchestration frameworks, multi-agent systems, and cross-platform AI integrations
• Develop guardrail specifications covering agent boundaries, tool access, data handling, autonomy, safety, and exception management
• Establish responsible AI controls for bias detection, explainability, transparency, auditability, model risk, and regulatory compliance
• Lead client architecture workshops, technical discovery sessions, design reviews, and executive-level solution discussions
• Define standards for AI-generated code quality, validation, security, testing, observability, and production readiness across the AI application development lifecycle
• Evaluate frontier models through structured benchmarking, red teaming, safety testing, and business-use-case validation
• Mentor AI engineers and architects while developing reusable reference architectures, accelerators, playbooks, and delivery standards

Requirements:

• 12–20 years of experience in enterprise technology, including significant leadership in AI architecture, solution architecture, or digital transformation
• Proven experience designing and delivering enterprise-scale Generative AI, RAG, LLM, and agentic AI solutions in production environments
• Strong hands-on software engineering experience with Java, .NET, Python, or comparable enterprise application technologies
• Deep understanding of multi-agent architectures, context engineering, knowledge orchestration, tool use, memory, planning, and human-agent collaboration patterns
• Experience defining responsible AI frameworks, agent guardrails, evaluation standards, audit controls, and regulated AI decisioning models
• Strong knowledge of cloud-native AI architecture, APIs, microservices, data platforms, DevSecOps, MLOps, AIOps, and enterprise integration patterns
• Experience evaluating frontier models, conducting AI red-team exercises, and defining AI quality, security, performance, and safety criteria
• Demonstrated ability to lead client architecture forums and advise executive, business, risk, and technology stakeholders
• Strong technical leadership, consulting, communication, stakeholder management, and business-outcome orientation
• Experience delivering AI solutions in regulated industries such as financial services, healthcare, life sciences, insurance, or government is preferred