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About the RoleAs a
Senior Manager - AI Engineer, you will play a critical hands-on leadership role in designing, building, and scaling enterprise-grade AI solutions. You will focus on LLM-powered systems, retrieval-augmented generation (RAG), and emerging agentic workflows, translating advanced AI concepts into production-ready applications.
You will be a key member of the AI & Data Consulting team, working closely with architects, clients, and engineering teams to deliver high-quality, scalable AI solutions that drive measurable business outcomes.
In this role, you will:- Design, develop, and deploy enterprise-grade AI/LLM solutions, including context handling, memory patterns, and prompt engineering strategies
- Build and optimize RAG pipelines, including embeddings, retrieval strategies, re-ranking, and evaluation frameworks for quality and performance
- Lead the development of agentic workflows and AI-powered applications, integrating APIs, enterprise tools, and data systems with appropriate guardrails
- Collaborate with architects and business stakeholders to integrate AI solutions with enterprise platforms (ERP, CRM, data platforms), ensuring security, scalability, and data integrity
- Own end-to-end engineering delivery, including code quality, testing, deployment, and performance optimization
- Provide technical leadership by mentoring junior engineers, conducting code reviews, and driving best practices in AI engineering and MLOps
- Partner with cross-functional teams to ensure alignment of AI solutions with business needs and production readiness standards
Work ModelWe strive to provide flexibility wherever possible. Based on this role's business requirements, this position requires travel as needed and a hybrid work model, with time spent in a client or Cognizant office in the United States. We are committed to supporting a healthy work-life balance through our wellbeing programs.
The working arrangements for this role are accurate as of the date of posting and may change based on project and client requirements.
What you must have to be considered- 8-12 years of experience in software engineering, AI/ML, or applied AI development, with strong hands-on expertise in Python-based systems
- Proven experience building and deploying LLM applications, including RAG architectures and vector databases
- Hands-on experience with LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, or equivalents)
- Strong understanding of prompt engineering, context design, and structured outputs, including security considerations such as prompt injection mitigation
- Experience developing scalable AI systems and APIs in cloud environments (AWS, Azure, or GCP)
- Demonstrated experience leading engineering teams or owning modules/workstreams in a delivery environment
- Strong problem-solving skills and ability to translate business requirements into technical solutions
These will help you succeed- Experience integrating AI solutions with enterprise systems, identity platforms (SSO/IAM), and secure data environments
- Familiarity with evaluation, observability, and monitoring tools for AI/LLM systems
- Experience with MLOps practices, CI/CD pipelines, and production deployment of AI applications
- Exposure to distributed systems and scalable cloud-native architectures
- Experience working in consulting or client-facing environments
- Advanced degree in Computer Science, Engineering, or related field is a plus
Why You'll Love This RoleYou'll have the opportunity to work on cutting-edge AI technologies, shape real-world enterprise AI solutions, and grow into broader technical leadership roles while working with a global team of experts.
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.
Compensation$130,000 - $158,500
This position is eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits- Medical, dental, vision, and life insurance
- 401(k) plan and contributions
- Employee stock purchase plan
- Employee assistance program
- 10 paid holidays plus PTO
- Paid parental leave and fertility assistance
- Learning and development certifications and programs
