About the role
As an AI Customer Engineer , you will make an impact by building scalable AI agent solutions and accelerating enterprise adoption of Generative AI technologies . You will be a valued member of the AI Engineering team and work collaboratively with architects, product teams, and cross-functional stakeholders to deliver intelligent, production-grade AI applications.
In this role, you will:
Build and deploy AI agents and GenAI-powered applications using modern frameworks and platforms
Design and implement RAG pipelines, prompt engineering workflows, and LLM integrations
Develop 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
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. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting ideas to this role.
