DGM - Full Stack AI Engineer / Sr.Architect

Overview

Full Stack AI Engineer position at Cognizant.

Responsibilities

• Collaborate with the Principal Architect to design and implement AI agents and multi-agent frameworks.
• Develop and maintain robust, scalable, and maintainable microservices architectures.
• Ensure seamless integration of AI agents , MCP Servers with core systems and databases.
• Develop APIs and SDKs for internal and external consumption.
• Work closely with data scientists to fine-tune and optimize LLMs for specific tasks and domains.
• Implement ML Ops practices, including CI/CD pipelines, model versioning, and experiment tracking1.
• Design and implement comprehensive monitoring and observability solutions to track model performance, identify anomalies, and ensure system stability2.
• Utilize containerization technologies such as Docker and Kubernetes for efficient deployment and scaling of applications3.
• Leverage cloud platforms such as AWS, Azure, or GCP for infrastructure and services3.
• Design and implement data pipelines for efficient data ingestion, transformation, and storage4.
• Ensure data quality and security throughout the data lifecycle5.
• Mentor junior engineers and foster a culture of innovation, collaboration, and continuous learning.

Qualifications

• 8-10 years of experience in software engineering with a strong focus on AI/ML.
• Proficiency in frontend frameworks like React, Angular, or Vue.js.
• Strong hands-on experience with backend technologies like Node.js, Python (with frameworks like Flask, Django, or FastAPI), or Java.
• Proven ability to design and implement complex, scalable, and maintainable architectures.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• Passion for continuous learning and staying up to date with the latest advancements in AI/ML.
• End-to-end experience with at least one full AI stack on Azure, AWS, or GCP, including components such as Azure Machine Learning, AWS SageMaker, or Google AI Platform3.
• Hands-on experience with agent frameworks like Autogen, AWS Agent Framework, LangGraph etc.
• Successfully led the development and deployment of an AI-powered recommendation system using AWS SageMaker, integrating it with a Node.js backend and a React frontend.
• Designed and implemented a real-time fraud detection system on Azure, utilizing Azure Machine Learning for model training and Kubernetes for container orchestration.