AI Engineer — AI Specialist

About Cognizant
Cognizant is a global leader in technology and business consulting with over 350,000 employees worldwide and revenues exceeding $19 billion. Serving Fortune 500 enterprises across banking, healthcare, retail, and manufacturing, Cognizant is rapidly expanding its AI Center of Excellence division. In 2026, the company is making massive investments in Generative AI and Agentic AI to deliver transformative enterprise solutions. This is one of the most active large-scale hirers of AI talent in the world right now.

Role Overview
As an AI Engineer specializing in Agentic and Generative AI, you will spearhead the delivery of intelligent, autonomous AI systems for Cognizant’s enterprise clients globally. You’ll serve as a hands-on technical expert and trusted advisor — designing, building, and deploying state-of-the-art AI solutions that use LLMs, multi-agent systems, and generative models to solve complex business challenges. You’ll bridge the gap between cutting-edge AI research and practical enterprise deployment.

Key Responsibilities

• Design and build end-to-end Agentic AI solutions using frameworks like LangChain, AutoGen, CrewAI, and Microsoft Semantic Kernel

• Develop GenAI-powered applications leveraging GPT-4, Claude, Gemini, and open-source LLMs

• Architect and implement RAG pipelines with enterprise knowledge bases, vector search, and hybrid retrieval

• Lead technical discovery sessions with enterprise clients to identify automation and AI opportunities

• Integrate AI agents into enterprise workflows including CRM, ERP, and customer support systems

• Design and implement multi-agent orchestration with tool use, memory, and planning capabilities

• Build, evaluate, and fine-tune foundation models on domain-specific datasets

• Define and monitor KPIs for AI system performance, safety, and business value delivery

• Collaborate with product managers, data engineers, and enterprise architects on delivery roadmaps

• Contribute to Cognizant’s internal AI Center of Excellence with best practices, documentation, and mentorship

Required Skills & Qualifications

• 4+ years of software engineering experience with a strong Python background

• 2+ years of hands-on experience with LLMs and GenAI development

• Proficiency in LangChain, LangGraph, or AutoGen frameworks

• Experience deploying ML models to production in cloud environments (Azure, AWS, GCP)

• Strong understanding of prompt engineering techniques, few-shot learning, and RLHF

• Knowledge of vector databases (Pinecone, Qdrant, FAISS)

• Excellent communication skills — ability to explain AI concepts to non-technical stakeholders