AI Customer Engineer
Cognizant
AI Customer EngineerAbout the roleAs 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 solutionsWork model: Work from OfficeAt 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 skillsThese 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
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