Engineering Manager

We are seeking a highly skilled and hands-on Engineering Manager – Backend (Python) to join our engineering team in Ahmedabad. The ideal candidate will bring deep technical expertise in building scalable backend systems, proficiency with modern cloud-native architectures, and proven experience leading high-performing engineering teams. This individual must be comfortable contributing to production-quality code, driving architectural decisions, and supporting the development of AI-enabled applications by leveraging FastAPI, LangGraph/Google ADK, and Gemini Enterprise on GCP. The Engineering Manager will oversee a team of backend engineers while remaining actively involved in technical execution. This is an exciting opportunity to lead mission-critical product engineering initiatives and build state-of-the-art AI-driven systems within a dynamic and innovative environment at Adani. Experience - 9–13 years of experience in product-based technology organizations. - Minimum 5 years of hands-on backend engineering experience using Python. - Served as an Engineering Manager or Technical Lead managing 10–15 engineers. - Demonstrated experience designing scalable microservices, cloud architectures, and distributed systems. - Strong exposure to building AI/LLM-enabled applications is preferred. Roles and Responsibilities As an Engineering Manager, you will be responsible for: Leadership & Delivery - Driving end-to-end design, development, testing, deployment, and maintenance of backend services and AI-enabled solutions. - Collaborating closely with product, architecture, data science, and AI teams to deliver high-impact features. Hands-on Engineering - Actively contributing to backend development using Python, FastAPI, and modular service design. - Designing, reviewing, and writing production-grade code, ensuring adherence to best practices and coding standards. - Creating skeletons, frameworks, and reusable components that accelerate backend engineering velocity. - Performing in-depth code reviews, debugging complex issues, and guiding engineers on technical excellence. Architecture & AI Platform Integration - Architecting scalable, secure, high-performing backend systems on GCP (Cloud Run, GKE, Cloud SQL). - Implementing AI/LLM workflows using LangGraph or Google ADK, integrating with Gemini Enterprise APIs. - Collaborating with AI/ML teams to integrate models into microservices with optimal latency and reliability. - Ensuring the backend architecture supports future scalability and multi-tenant enterprise use cases. Strategic Contributions - Acting as a thought leader in backend architecture, cloud-native design, and AI-driven application development. - Contributing to roadmap planning, resource allocation, and execution strategy aligned with business objectives. - Staying up to date with emerging Python frameworks, LLM orchestration technologies, and GCP innovations. Education Qualification - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline. Behavioural Skills - Strong leadership capabilities and experience managing multi-disciplinary technical teams. - Excellent communication and stakeholder management skills. - Strategic, analytical, and problem-solving mindset. - Demonstrated ability to thrive in a fast-paced, innovation-driven environment. - High adaptability and openness to continuous learning. Technical Skills - Expertise in Python backend engineering, FastAPI, asynchronous programming, and microservices. - Strong understanding of LangGraph or Google ADK for LLM workflow orchestration. - Proficiency with GCP services including Cloud Run, GKE, Cloud SQL, IAM, VPC, Pub/Sub, and Cloud Storage. - Experience integrating AI/LLM systems such as Gemini Enterprise into backend applications. - Strong fundamentals in system design, architecture, scalability, and performance optimization. - Hands-on exposure to DevOps, CI/CD pipelines, Docker, Kubernetes, and cloud-native best practices. Non-Negotiable Skills - Demonstrable hands-on backend engineering expertise in Python and FastAPI. - Proven experience managing 10–15-member engineering teams. - Strong grounding in cloud-native architecture and production deployment workflows. - Ability to contribute directly to development while leading teams effectively.