AI Engineer

As an AI Engineer at Zensar Technologies, you will be at the forefront of our AI initiatives. Your primary focus will be on designing and developing AI models and applications, utilizing your expertise in various AI technologies. You will collaborate with a dynamic team of engineers and data scientists to create innovative solutions that drive our business forward. This role offers an exciting opportunity to work with cutting-edge technologies and make a significant impact on our AI-driven projects.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• 3+ years of experience in AI engineering, with a strong background in machine learning and deep learning.
• Proficiency in programming languages such as Python, and experience with AI frameworks like Langgraph and Agentic AI.
• Hands-on experience with MCP servers and an understanding of cloud computing environments.
• Knowledge of AgentOps, AI Security Guardrails, and Google A2A is highly advantageous.
• Familiarity with FastAPI or similar web frameworks for building AI-powered APIs.
• Strong problem-solving and analytical skills, with the ability to think critically and creatively.
• Excellent communication and collaboration skills, with a track record of working effectively in a team environment.
• A passion for staying updated with the latest AI trends and a desire to contribute to innovative projects.

• Design and develop AI models and applications using Langgraph, Agentic AI, and Multi-Agent frameworks.
• Implement and integrate AI solutions on MCP servers, ensuring optimal performance and scalability.
• Collaborate with cross-functional teams to understand business requirements and translate them into AI-powered solutions.
• Build and maintain AgentOps and AI Security Guardrails to ensure the secure and ethical use of AI technologies.
• Stay updated with the latest advancements in AI and machine learning, and incorporate them into our projects.
• Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
• Document and communicate AI project progress, providing regular updates to stakeholders.
• Mentor and guide junior team members, fostering a culture of knowledge sharing and collaboration.
• Identify and mitigate risks associated with AI projects, ensuring timely delivery and high-quality outcomes.