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.

Experience
8-12 yrs