Engineering Manager
Drive engineering excellence at scale. Lead high-impact teams, shape platform strategy, and build resilient, future-ready systems.
Minimum Qualifications
- B.E / B.Tech (preferred)
- 12–18+ years of experience in engineering, solution architecture, or platform leadership
- 5+ years of hands-on technical leadership and people management experience
- Strong hands-on experience in TypeScript, Node.js, React.js, Next.js, AWS, and Apache suite
- Proven experience working in large-scale product/platform organizations (preferably global/regulatory environments)
- Strong experience leveraging AI in SDLC workflows, including GitHub Copilot, Cursor, AI-assisted code reviews, guardrail systems, and prompt engineering frameworks
Role Overview
As a Engineering Manager, you will lead high-performing engineering teams while driving platform strategy, architectural alignment, AI-enriched SDLC adoption, and product excellence. You will work closely with Product, Architecture, and Business teams to deliver scalable, high-quality solutions in a fast-paced environment.
Key Responsibilities
Technical Leadership & Strategy
- Define and drive technology strategy, architecture roadmaps, and platform vision
- Translate business goals into scalable and actionable engineering solutions
- Manage technical standards, upgrade roadmaps, version control, and engineering backlogs
- Connect architectural components across systems to ensure cohesive platform design
- Support platform solutions that extend beyond individual teams to the broader ecosystem
- Introduce and institutionalize AI-driven SDLC frameworks, including Copilot adoption strategy, prompt libraries, coding templates, quality guardrails, security constraints, and model usage guidelines
- Evaluate and integrate AI coding assistants (GitHub Copilot, Cursor, etc.) into engineering workflows to accelerate design, development, and documentation
Engineering Excellence
- Own and track key engineering metrics (quality, performance, scalability, delivery)
- Drive engineering best practices, governance, and standardization
- Ensure strong code quality, reusable components, and system resilience
- Troubleshoot design challenges and guide teams toward cost-effective, high-quality solutions
- Work at scale and speed, ensuring efficient and reliable delivery
- Implement AI-powered code quality automation, test generation, and code-review pipelines
- Establish engineering guardrails for ethical AI usage, data confidentiality, prompt safety, and validation mechanisms
- Drive adoption of reusable AI prompt banks, coding accelerators, architectural templates, and cross-team engineering patterns
Team Leadership & Talent Development
- Lead, mentor, and grow high-performing engineering teams
- Identify skill gaps, maintain skill matrix, and drive training initiatives
- Support talent planning and future capability building
- Act as both a technical advisor and process coach to engineering teams
- Upskill teams on AI-first engineering practices, responsible AI usage, prompt engineering, and AI toolchains
- Establish L&D programs focused on Copilot effectiveness, AI debugging, and accelerated delivery using AI tools
Collaboration & Stakeholder Management
- Partner closely with Product Managers, Technical Leads, and Business teams
- Drive cross-functional collaboration and alignment across domains
- Influence stakeholders and enable data-driven decision-making frameworks
- Ensure alignment between product, engineering, and business operations
- Evangelize AI-led ways of working across business, architecture, and engineering stakeholders
Delivery & Execution
- Lead complex technical projects and platform initiatives
- Contribute to product strategy and roadmap execution
- Establish quality benchmarks for internal teams and external vendors
- Guide teams in building prototypes, blueprints, and scalable solutions
- Implement AI-based accelerators for design documentation, test case generation, estimation models, and development workflows
- Ensure consistent usage of AI-enabled development templates, automated review pipelines, and SDLC automation tools
Strategic & Leadership Skills
- Strong ability to balance speed, cost, architecture quality, and long-term sustainability
- Expertise in governance models, decision frameworks, and platform alignment
- Proven ability to drive multi-platform transformation programs
- Strong stakeholder management and influencing skills
- Ability to shape organizational adoption of AI-driven engineering, define governance, and maintain high bar for responsible usage
- Champion AI-first engineering culture grounded in safety, guardrails, and continuous productivity gains
Success Measures
- Well-defined multi-year platform strategy aligned with business goals
- Reduced architectural fragmentation and improved time-to-market
- High adherence to engineering standards and enterprise guidelines
- Enhanced scalability, performance, and system resilience
- Strong, aligned, and high-performing engineering culture
- Demonstrable efficiency improvements leveraging AI (velocity, quality, cycle time)
- Consistent usage of AI frameworks, prompt libraries, templates, and SDLC automation across teams
Interested candidates, please share your updated resume at [Confidential Information]
