11 hours ago
Base Salary
$175k - $205k/yr
Responsibilities
- Design and deliver AI-native enterprise architectures spanning applications, data platforms, business processes, and cloud environments.
- Build and operationalize production-grade Generative AI, RAG, LLM, and agentic AI solutions from architecture through deployment and ongoing operation.
- Define human-agent operating models, capability matrices, escalation paths, human-in-the-loop controls, context pipelines, knowledge orchestration frameworks, and multi-agent systems.
- Develop guardrails for 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 technical discussions.
- Define AI application lifecycle standards for code quality, validation, security, testing, observability, and production readiness.
- Evaluate frontier models through benchmarking, red teaming, safety testing, and business-use-case validation.
- Mentor AI engineers and architects and develop 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.
- 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.
- Ability to lead client architecture forums and advise executive, business, risk, and technology stakeholders.
- Experience delivering AI solutions in regulated industries such as financial services, healthcare, life sciences, insurance, or government is preferred.
- Strong technical leadership, consulting, communication, stakeholder management, and business-outcome orientation.
Benefits
- Medical, dental, vision, and life insurance, subject to eligibility requirements.
- Paid holidays and paid time off.
- 401(k) plan and contributions.
- Long-term and short-term disability coverage.
- Paid parental leave.
- Employee Stock Purchase Plan.
- Eligible for Cognizant’s discretionary annual incentive program based on performance and applicable plan terms.
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.