- Lead high-impact teams, shape platform strategy, and build resilient, future-ready systems.

Job location - Malad, Mumbai

Minimum Qualifications :

- B.E / B.Tech (preferred)

- 12 to 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 Technical 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