Summary
✨ AI‑Generated
A technical leadership role responsible for guiding cloud-native software delivery, defining engineering standards, mentoring teams, and ensuring secure, reliable, and scalable enterprise solutions.
Highlights
Leadership opportunity combining hands-on architecture, team mentoring, cloud engineering, and strategic technology planning.
Description
Position Summary
The Engineering Lead is responsible for leading the design, development, delivery, and operational excellence of a cloud-native enterprise software product running on Microsoft Azure.
This role provides technical leadership to cross-functional engineering teams, establishes engineering standards and architecture guardrails, and ensures delivery of scalable, secure, reliable, and AI-enabled solutions.
The Engineering Lead partners closely with Product Management, Solution Architecture, DevOps, Security, UX, Data, and AI engineering teams to deliver innovative software capabilities that create measurable business value.
The role combines hands-on technical leadership with people leadership, mentoring, and strategic technology planning.
Key Responsibilities
Technical Leadership Product Delivery Cloud Engineering & Operations
• Own the overall technical delivery of one or more product domains.
Lead architecture and design decisions for cloud-native solutions running on Microsoft Azure.
• Ensure adherence to engineering standards, security requirements, and enterprise architecture principles.
• Drive software quality through code reviews, design reviews, testing strategies, and engineering best practices.
• Provide technical guidance and mentorship to development teams.
Collaborate with Product Managers and Architects to translate business requirements into scalable technical solutions.
• Lead sprint planning, backlog refinement, estimation, and execution activities.
• Identify and mitigate technical risks and delivery dependencies.
• Drive successful delivery of product releases while balancing quality, cost, and schedule.
Lead development of microservices, APIs, event-driven architectures, and distributed systems.
• Ensure solutions are designed for reliability, availability, scalability, and observability.
• Partner with DevOps teams to implement CI/CD pipelines and infrastructure automation.
• Monitor platform health, performance, security, and operational metrics.
AI and Intelligent Solutions
Drive adoption of AI capabilities within products and engineering practices.
Evaluate opportunities to leverage Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), Copilot technologies, and machine learning services.
• Guide implementation of Azure AI services, agent frameworks, vector databases, AI search, and intelligent workflow automation.
• Establish responsible AI practices including governance, security, transparency, testing, and compliance.
• Promote AI-assisted engineering practices to improve developer productivity and software quality.
• Build, mentor, and develop high-performing engineering teams.
• Foster a culture of accountability, innovation, collaboration, and continuous improvement.
• Support hiring, onboarding, performance development, and career growth of engineers.
• Encourage knowledge sharing and engineering excellence across teams.
• Partner with business stakeholders, product leaders, and technology leadership.
• Communicate technical direction, delivery plans, risks, and status effectively.
• Influence strategic technology decisions and roadmap planning.
