Custom Software Engineering Lead

Project Role : Custom Software Engineering Lead Project Role Description : Own the technical direction and architecture of custom software solutions, leading teams through design and delivery. Set development standards and ensure code quality, scalability, and performance aligned to business objectives. Must have skills : Python (Programming Language) Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education

Summary: Own the technical design and implementation of the AI agent builder platform. You ll work closely with the manager and senior engineers to define reusable components, frameworks, and best practices for agent development. Roles and Responsibilities Architect and implement core components of the AI agent builder. Develop and deploy AI agents for internal and external business workflows. Design reusable modules for agent orchestration, memory, and tool integration. Collaborate with engineers to ensure consistency and scalability across agent implementations. Evaluate and integrate Azure AI services and open-source libraries. Contribute to technical documentation and internal developer enablement. Monitor and optimize agent performance and reliability. Participate in code reviews, testing, and documentation. Technical experience & Professional attributes: 10+ years in software engineering with 5+ years in AI/ML systems. Deep experience with Python, Azure ML, and LLM-based agent frameworks. Strong understanding of prompt engineering, RAG, and agent lifecycle. Experience with CI/CD, containerization, and cloud-native development. Excellent communication and stakeholder management skills. Strong experience in building production-level systems implementing DevOps best practices. Thorough understanding of best practices regarding agile software development and software testing. Experience of deploying cloud-based applications using automated CI/CD processes and container technologies. Understanding of security best practices when architecting SaaS applications on cloud Infrastructure. Ability to understand complex business systems and a willingness to learn and apply new technologies as needed.