AI Customer Engineer

•  scalable backend services and APIs for AI-driven systems
• Enable cloud-native deployments with containerization and microservices architecture
• Collaborate with cross-functional teams to deliver reliable, secure, and high-performing AI solutions

Work model: Work from Office

At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role’s business requirements, this is an onsite position requiring 5 days a week in a client or Cognizant office in [Chennai/Bangalore].

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured, we will always be clear about role expectations.

What you need to have to be considered

• Hands-on experience to Google ADK or CoPilot Studio in building AI Agents (or any tool such as CrewAI, Autogen for building agents)
• Hands-on working knowledge in defining and configuring prompts, instructions, tools, reasoning, guardrails and other similar concepts in AI Agent development
• Strong experience with RAG pipelines, Vector DBs, tokenization, and prompt engineering
• Hands-on experience in creating and maintaining Python libraries, utilize LangChain, Hugging Face, OpenAI API, or local models
• Very strong experience with developing RESTful APIs in Python using frameworks like FastAPI and integrate third-party services, UI components and APIs
• Hands-on working with Docker-based deployments, and leveraging GitHub for code repo and version control is MUST
• Interpret microservices design principles and cloud computing basics
• Strong communication skills and articulation skills

These will help you stand out

• Experience working on end-to-end AI/GenAI project lifecycle
• Exposure to enterprise-scale deployments and production-grade AI systems
• Ability to optimize performance, scalability, and reliability of AI models and services
• Strong collaboration skills across engineering, product, and business teams
  • Adaptability to rapidly evolving AI tools, frameworks, and standards