AI Customer Engineer

About The Role

As an AI Customer Engineer, you will make an impactful difference 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, collaborating 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

This is an onsite position, requiring 5 days a week in a client or Cognizant office located in [Chennai/Bangalore]. Please note that working arrangements may change based on project requirements and business needs. We strive to provide flexibility wherever possible through our various wellbeing programs.

To Be Considered, You Need:

• Hands-on experience with Google ADK or CoPilot Studio in building AI Agents (or similar tools like CrewAI, Autogen).
• Strong knowledge of defining and configuring prompts, instructions, tools, reasoning, guardrails, and related concepts.
• Experience with RAG pipelines, Vector DBs, tokenization, and prompt engineering.
• Ability to create and maintain Python libraries using LangChain, Hugging Face, OpenAI API, or local models.
• Very strong experience developing RESTful APIs in Python (e.g., FastAPI) and integrating third-party services/UI components.
• Proficiency with Docker-based deployments and GitHub for version control (MUST HAVE).
• Familiarity with microservices design principles and cloud computing basics.

Differentiators We Look For:

Experience working on end-to-end AI/GenAI project lifecycles, exposure to enterprise-scale deployments, ability to optimize performance/scalability, strong communication skills for collaboration across teams, and adaptability to rapidly evolving AI tools.