AI Engineer

About the Role

You will serve as an AI Engineer working at InfoBeans, located in Pune or Indore, contributing to application of artificial intelligence in engineering and business workflows. Your focus will be on rapid prototyping, validating concepts, enabling reuse, and facilitating adoption into production environments. Collaborating directly with client engineering leaders, you will independently design solutions, develop reusable agentic frameworks, and optimize engineering processes.

Key Responsibilities

• Create software development lifecycle (SDLC) agents and develop a reusable library of skills and instructions.
• Integrate agent-assisted pull request reviews, development, testing, and related engineering workflows to increase efficiency.
• Document and codify reusable prompts, skill sets, design patterns, and implementation knowledge.
• Support automation initiatives related to Databricks Lakehouse where AI can add significant value.
• Contribute to AI enhancements for credit-risk applications as opportunities become available.
• Work autonomously with client engineering leads to craft innovative solutions.

Skills and Experience Required

• Strong proficiency in Python programming and application development.
• Hands-on experience with Generative AI (GenAI) and agent-based development methodologies.
• In-depth knowledge of APIs, data integration techniques, Git and CI/CD pipelines, and cloud architecture principles.
• Experience working with Azure cloud platform and big data tools such as Databricks or Snowflake.
• Familiarity with Claude Code or GitHub Copilot and applying spec-driven development processes.
• Demonstrated ability to independently engage with client engineering teams to define and deliver solutions.
• Good judgment on choosing the appropriate automation strategies between agents and traditional engineering methods.

Why Join This Role

• Engage with cutting-edge Generative AI and agentic frameworks, enhancing hands-on technical expertise.
• Directly influence client projects and take responsibility for solution architecture and engineering workflows.
• Be part of a culture that values rapid prototyping, effective automation, and adoption of high-value production technologies.
• Gain exposure to leading cloud and big data platforms including Azure, Databricks, and Snowflake.