Engineering Manager

Requirements:

• B. Tech / M. Tech in Computer Science, Software Engineering, or a related discipline.
• 8-10 years of total software engineering experience with a strong backend focus, of which at least 2 years in a Tech Lead, Engineering Lead, or Engineering Manager role.
• Deep hands-on expertise in Java (17+) and the Spring ecosystem Spring Boot (3 x / 4 x), Spring Security, Spring Data, Spring Cloud, Spring WebFlux (reactive). Ability to write production-grade code, not just review it.
• Strong experience designing and building microservices architectures, RESTful APIs, event-driven systems (Kafka / RabbitMQ), and database layers (PostgreSQL, MongoDB, Redis).
• Proven track record of building applications from the ground up in greenfield product development in a SaaS or product-company context, taking features from whiteboard to production.
• Experience leading and managing teams of both backend and frontend engineers, comfortable reviewing React / TypeScript code, guiding frontend architecture decisions, and maintaining full-stack delivery velocity.
• Hands-on experience running Scrum / Agile processes: sprint planning, backlog management, velocity tracking, and retrospectives with a practical, outcome-driven approach (not ceremony for ceremony's sake).
• Strong DevOps and deployment experience with Docker, Kubernetes, CI/CD pipelines (GitHub Actions / GitLab CI / Jenkins), and at least one major cloud platform (AWS preferred; Azure / GCP also valued).
• Solid understanding of system design fundamentals: caching strategies, load balancing, rate limiting, database indexing, horizontal scaling, and high-availability patterns.
• Experience in a high-growth start-up or similarly fast-paced environment where shipping speed, scrappiness, and wearing multiple hats are the norm.
• Excellent communication skills able to articulate technical trade-offs to product and business stakeholders, write clear RFCs and design documents, and present to leadership.

Good to Have:

• Experience with industrial IoT, manufacturing systems, or integration with factory-floor protocols (OPC-UA, MQTT, Modbus) and SCADA / PLC systems.
• Familiarity with Python for scripting, data pipelines, or lightweight services useful for collaborating with the AI / Data Science team.
• Exposure to AI / ML serving infrastructure, model APIs, feature stores, inference caching and an understanding of how backend systems integrate with computer vision or LLM pipelines.
• Experience with multi-tenant SaaS architecture, tenant isolation, role-based access control, and enterprise security compliance (SOC 2 ISO 27001).
• Knowledge of Java 21+ virtual threads (Project Loom) and reactive programming (Spring WebFlux, Project Reactor) for high-concurrency workloads.
• Familiarity with Infrastructure-as-Code (Terraform, Pulumi) and GitOps workflows for managing multi-cloud and on-premises deployments.
• Experience with performance engineering, JVM tuning, garbage collection profiling, load testing (JMeter, k6 Gatling), and database query optimisation at scale.

Skills

AWS, Azure, Docker, Engineering Lead, Engineering Manager, GCP, Java, Kafka, Kubernetes, Spring, Spring Boot, Tech Lead, microservices