: ENGINEERING LEAD

Location: Pune – S.B. Road

Department: Technology / Engineering

Experience: 10–20 Years

Role: Engineering Lead

About Repos

Repos is redefining energy distribution through technology, innovation, and intelligent solutions. By combining technology, data, and operational excellence, we are building solutions that address complex real-world challenges across the energy ecosystem.

We are looking for an Engineering Lead who can translate business vision into robust technology solutions, lead high-performing engineering teams, and drive innovation across backend systems and AI-powered applications.

Role Overview The Engineering Lead will own the technical direction, architecture, development, and delivery of scalable software solutions. This role requires strong expertise in Python, Django, and AI/ML, along with proven experience in software architecture, backend engineering, team leadership, and end-to-end product development.

The ideal candidate will combine deep technical expertise with strategic thinking, driving engineering excellence while ensuring that technology solutions are reliable, secure, scalable, and aligned with business objectives.

Key Responsibilities

1. Engineering Leadership and Technical Strategy

- Define and execute the engineering roadmap in alignment with business and product priorities.
- Lead the design, development, deployment, and continuous improvement of scalable software applications and technology platforms.
- Establish engineering standards, architectural principles, coding practices, and development guidelines.
- Evaluate emerging technologies and identify opportunities to improve system performance, scalability, and operational efficiency.
- Drive technical decision-making, balancing innovation, maintainability, performance, and delivery timelines.

2. Backend Development and Architecture

- Lead the development of robust backend applications and services using Python and Django.
- Design scalable application architectures, RESTful APIs, microservices, and integrations with internal and external systems.
- Oversee database design, data modelling, query optimisation, and application performance.
- Ensure the reliability, security, maintainability, and scalability of backend systems.
- Establish best practices for code quality, version control, testing, documentation, and code reviews.
- Identify technical bottlenecks and lead initiatives to improve application performance and system resilience.

3. AI/ML Engineering and Innovation

- Identify business opportunities where Artificial Intelligence and Machine Learning (AI/ML) can improve operational efficiency, automation, decision-making, and customer experience.
- Lead the integration of AI/ML capabilities into existing applications and new technology products.
- Collaborate with data scientists, product teams, and engineers to move AI/ML solutions from experimentation to production.
- Oversee the development and integration of intelligent models, data-driven applications, and automated workflows.




- Ensure appropriate practices for model deployment, performance monitoring, data quality, scalability, and responsible use of AI.
- Evaluate emerging AI/ML frameworks, tools, and approaches to identify opportunities for practical business impact.

4. Product Development and Delivery

- Partner with product managers and business stakeholders to translate requirements into technical solutions and actionable engineering plans.
- Drive end-to-end delivery, from solution design and development to testing, deployment, and production support.
- Establish efficient development workflows, release processes, and CI/CD practices.
- Ensure timely delivery of high-quality software while maintaining engineering standards.
- Monitor application performance, production issues, and technical risks; drive timely resolution and continuous improvement.
- Promote a culture of automation, reliability, and continuous delivery across engineering teams.

5. Team Leadership and Talent Development

- Lead, mentor, and develop engineering teams, fostering technical excellence, accountability, and collaboration.
- Build a culture of ownership, innovation, continuous learning, and engineering discipline.
- Guide team members on architecture, coding standards, problem-solving, and technical decision-making.
- Work closely with cross-functional teams, including Product, Data, DevOps, and Business, to ensure aligned execution.
- Support engineering capacity planning, technical estimations, prioritisation, and resource allocation.
- Identify capability gaps and drive upskilling initiatives to strengthen the team's technical capabilities.

6. Quality, Security, and Operational Excellence

- Establish robust practices for automated testing, code quality, application monitoring, and defect prevention.
- Ensure applications follow appropriate security, access-control, and data-protection practices.
- Drive cloud readiness, deployment automation, system observability, and production reliability.
- Establish measurable engineering KPIs covering delivery predictability, system performance, reliability, and maintainability.
- Identify and address technical debt through structured improvement initiatives.

Required Technical Skills

- Python: Strong hands-on expertise in Python programming, application development, and software engineering best practices.
- Django: Proven experience building, architecting, and scaling backend applications using Django and its associated ecosystem.
- AI/ML: Practical experience developing, integrating, or deploying AI/ML solutions in production or business-critical applications.
- Backend Architecture:



Strong understanding of RESTful APIs, microservices, distributed systems, and scalable application design.
- Databases: Experience with relational databases such as PostgreSQL or MySQL, including schema design and query optimisation.
- Software Engineering: Strong understanding of data structures, algorithms, design patterns, clean code, testing, and code reviews.
- Cloud and DevOps: Familiarity with cloud platforms, containerisation, CI/CD pipelines, deployment processes, and application monitoring.
- System Design: Ability to design secure, high-performing, resilient, and scalable technology systems.

Preferred Skills

- Experience integrating generative AI, large language models (LLMs), or AI-powered automation into production applications.
- Familiarity with AI/ML frameworks and libraries such as PyTorch, TensorFlow, or scikit-learn.
- Experience with asynchronous processing, message queues, background tasks, and event-driven architectures.
- Exposure to Docker, Kubernetes, AWS, Azure, or Google Cloud Platform.
- Understanding of data pipelines, model-serving architecture, and production ML lifecycle management.
- Experience working in product-led, high-growth, or technology-driven organisations.

Qualifications and Experience

- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline.
- 10–20 years of overall experience in software engineering, backend development, or technology delivery.
- Solid hands-on experience in Python and Django, with the ability to guide architecture and resolve complex technical challenges.
- Demonstrated experience in AI/ML development, integration, or implementation.
- Prior experience leading engineering teams, managing technical roadmaps, and delivering complex software products.
- Proven ability to work with senior stakeholders and translate business objectives into scalable engineering solutions.

Key Success Measures

- Successful delivery of scalable, reliable, and maintainable technology solutions.
- Effective adoption of AI/ML capabilities that create measurable business value.
- Improved application performance, system reliability, and operational efficiency.
- Consistent delivery against engineering roadmaps and business priorities.
- Strong engineering practices, reduced technical debt, and improved development productivity.
- High-performing engineering teams with clear ownership and strong technical capabilities.

What We Value We value leaders who combine technical depth with strategic thinking, take ownership of outcomes, and build teams that consistently deliver meaningful impact. The ideal candidate is comfortable navigating complex technical challenges, challenging conventional approaches, and translating innovative ideas into scalable solutions.

If you are passionate about engineering excellence, building intelligent systems, and leading technology that solves real-world problems, we would like to hear from you.

📌 Engineering Lead (Maharashtra)
🏢 Repos Energy
📍 Maharashtra