Engineering Manager

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 [HIDDEN TEXT]