Engineering Manager - .Net/Java

Key Responsibilities :

- Lead and manage engineering teams responsible for designing, developing, and delivering enterprise-grade applications using .

- Drive the adoption and integration of Generative AI capabilities across application development and engineering workflows.

- Guide teams in building AI-powered solutions using LLMs, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.

- Oversee the transition of AI/GenAI solutions from proof of concept (POC) to production deployment.

- Promote AI-powered Software Development Lifecycle (SDLC) practices to improve engineering productivity, development efficiency, and code quality.

- Define and manage engineering roadmaps, technical priorities, and delivery plans in alignment with business objectives.

- Drive Agile/Scrum practices, including backlog management, sprint planning, delivery tracking, and continuous improvement.

- Work closely with product owners, architects, business stakeholders, and cross-functional teams to ensure successful execution.

- Ensure adherence to software architecture principles, coding standards, security requirements, and engineering best practices.

- Oversee cloud-native application development, microservices architecture, DevOps practices, and deployment processes.

- Monitor engineering performance metrics, delivery quality, productivity, and team effectiveness.

- Mentor engineering teams, support technical development, and foster a culture of collaboration and continuous learning.

Mandatory Skills & Qualifications :

- Strong hands-on development background in .NET and/or Java.

- Proven experience in software engineering team leadership and people management.

- Practical exposure to Generative AI, LLMs, RAG, and Agentic AI.

- Experience implementing or integrating AI-driven solutions into enterprise applications.

- Experience taking AI/GenAI solutions from POC to production.

- Understanding of AI-powered SDLC practices and AI-assisted software engineering.

- Strong understanding of Agile/Scrum methodologies, backlog management, sprint planning, and delivery management.

- Experience with product operating models, stakeholder management, and cross-functional team leadership.

- Good understanding of cloud platforms, microservices, DevOps, and modern software architecture.

- Excellent communication, analytical, problem-solving, and people management skills.

Good-to-Have Skills :

- Certifications in Scrum, ITIL, TOGAF, or other Agile methodologies.

- Experience working with Jira and Azure DevOps.

- Familiarity with engineering performance metrics, delivery dashboards, and productivity measurement.

- Exposure to cloud-native architecture and enterprise-scale application modernization.

- Experience driving engineering transformation and adoption of emerging technologies