Job Description

Position Summary

As an Engineering Lead, you will provide technical leadership for the design, development, and delivery of scalable digital and AI-enabled solutions. You will lead engineering teams, make architecture and technology decisions, ensure delivery quality, and partner with business and client stakeholders to translate strategic objectives into practical technology solutions.

You will work across front-end, back-end, cloud, data, and AI capabilities to deliver production-grade solutions for Human Capital and other Deloitte offerings.

What You'll Do

Technical Leadership

- Define and govern technical architecture for complex web, cloud, data, and AI-enabled applications.
- Establish engineering standards, development practices, design patterns, and technology roadmaps.
- Make informed decisions regarding frameworks, platforms, integrations, scalability, security, and maintainability.
- Lead architecture and design reviews and ensure solutions meet functional and non-functional requirements.
- Guide teams in developing production-ready applications using MERN, Python, SQL, AI, and Generative AI technologies.
- Ensure appropriate use of APIs, microservices, event-driven patterns, cloud services, and integration frameworks.

Delivery Ownership

- Own end-to-end engineering delivery across planning, design, development, testing, deployment, and post-production support.
- Translate business and client requirements into actionable technical approaches, estimates, workplans, and deliverables.
- Identify delivery risks, dependencies, technical debt, and resource constraints, and drive timely resolution.
- Establish quality gates for code quality, test coverage, performance, security, and release readiness.
- Coordinate with product, UX, QA, Dev Ops, data, cybersecurity, and client teams.
- Support multiple workstreams and ensure consistent delivery across onshore and offshore teams.

Team Leadership and Development

- Lead, coach, and mentor engineers, consultants, and developers across different experience levels.
- Allocate work based on capability, delivery priorities, and development objectives.




- Conduct technical knowledge-sharing sessions and promote continuous learning.
- Provide constructive feedback and contribute to performance and career development discussions.
- Build a culture of collaboration, accountability, engineering excellence, and continuous improvement.
- Support recruitment, technical interviews, onboarding, and capability development where required.

Stakeholder and Client Management

- Serve as a trusted technical advisor to business and client stakeholders.
- Explain complex technical concepts, architecture decisions, risks, and trade-offs to both technical and non-technical audiences.
- Facilitate technical workshops, requirement discussions, solution demonstrations, and design sessions.
- Partner with leadership to identify opportunities for innovation, reuse, automation, and asset development.
- Contribute to proposals, solution estimates, technical qualifications, and client presentations.

Engineering Excellence

- Promote secure, scalable, maintainable, and testable software development practices.
- Oversee code reviews, automated testing, CI/CD, observability, monitoring, and production support processes.
- Ensure appropriate documentation of architecture, APIs, data flows, deployment procedures, and operational considerations.
- Drive resolution of complex issues spanning the UI, APIs, databases, cloud infrastructure, and deployment environments.
- Stay current with developments in full-stack engineering, cloud platforms, AI, Generative AI, and software delivery practices.
- Travel as required by project and client needs.

Required Technical Skills

- Strong hands-on experience with Python, SQL, ReactJS, Node.js, and Express.js.




- Experience designing and delivering full-stack applications using MERN and Python-based technologies.
- Experience with AI and Generative AI solutions, including:
- Large language models
- Prompt engineering
- Retrieval-Augmented Generation
- Vector databases
- Lang Chain or Llama Index
- Production deployment of LLM-enabled features

- Experience with application architecture, APIs, integration patterns, databases, cloud services, and CI/CD.
- Experience with software engineering practices including code reviews, automated testing, version control, deployment, monitoring, and technical documentation.
- Ability to evaluate technology choices and provide transparent recommendations based on business and engineering needs.

Preferred Skills

- MongoDB, Pandas, Snowflake, or comparable data technologies.
- Experience with AWS, Azure, or other public cloud platforms.
- Experience with containerization, Kubernetes, serverless technologies, or event-driven architecture.
- Experience with AI coding-assistance tools such as Git Hub Copilot, Claude Code, or similar.
- Experience building reusable platforms, accelerators, frameworks, or internal technology assets.
- Experience working in consulting, client-facing, or distributed delivery environments.

Experience

- Typically 10+ years of experience in software engineering, full-stack development, solution architecture, or a related field.
- Demonstrated experience leading engineering teams and delivering complex applications from concept through production.
- Experience managing technical delivery across multiple teams, workstreams, or client engagements.
- Demonstrated ability to balance hands-on technical contribution with team leadership and stakeholder management.

Education

BE/B. Tech, MCA, M. Sc. in Computer Science, Engineering, Information Technology, or a related discipline.

Core Competencies

- Technical vision and architecture
- Engineering delivery management
- Team leadership and mentoring
- Client and stakeholder management
- Structured problem-solving
- Executive communication
- Quality and operational discipline
- Innovation and continuous improvement

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