About the Role
We are looking for a SR AI Engineer to design, build, and scale Generative AI solutions that automate processes and power conversational assistants, including Retrieval‑Augmented Generation (RAG) and agent‑based systems.
In this role, you will work end‑to‑end, from discovery and prototyping to production deployment and operation with real users. You will architect cloud‑native solutions on Azure and/or AWS, integrate with enterprise platforms, and balance quality, safety, cost, and performance. This is a hands‑on senior role with the opportunity to lead technical initiatives and shape best practices across projects.
Key Responsibilities
- Engage directly with client stakeholders to identify, refine, and prioritize Generative AI use cases.
- Act as a technical lead, defining architecture, quality standards, and best practices for AI solutions.
- Architect robust GenAI solutions on Azure and/or AWS, including LLM orchestration, RAG, API integrations, security, observability, and cost control.
- Design and deliver conversational assistants and copilots, covering prompt design, tool calling, grounding strategies, guardrails, and memory management.
- Implement and optimize RAG pipelines: ingestion, chunking, embeddings, vector stores, retrieval evaluation, reranking, caching, and latency optimization.
- Evaluate and harden agentic systems using quality, robustness, and groundedness metrics.
- Own LLMOps/MLOps practices in production environments, including containerization, monitoring, and performance tracking.
Required Skills & Qualifications
- Bachelor’s, Master’s, or PhD in Machine Learning, Computer Science, Engineering, Mathematics, or related fields.
- Proven experience in senior AI engineering roles with strong exposure to Generative AI.
- Extensive experience designing and scaling GenAI applications, including RAG architectures and autonomous or agent‑based systems.
- Strong cloud experience on Azure and/or AWS (IAM, networking, compute, storage, monitoring, security, cost management).
- Solid software engineering skills in Python, including API integration, testing, code reviews, and documentation.
- Strong product and business mindset, able to define KPIs and clearly communicate impact to non‑technical stakeholders.
Nice to Have
- Experience leading small technical teams or mentoring other engineers.
- Exposure to deep learning frameworks such as PyTorch or TensorFlow.
- Hands‑on experience with LLMOps/MLOps in production environments.
- Azure or AWS AI/ML certifications.
- Background in IT consulting or client‑facing environments.
About us
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, building the bridge between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, realize tangible returns and keep global enterprises ahead in a fast-changing world. See how at www.cognizant.com or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.
