Engineer Manager (VP / AVP)

We are looking for an Engineering Manager with a strong backend pedigree to lead a cross-functional team of backend and frontend engineers. You will own the full product engineering lifecycle from greenfield architecture and ground-up development through to production operations at scale for an industrial AI SaaS platform. The platform powers real-time decision automation on factory floors across steel, cement, pharma, and paints, ingesting high-volume sensor and vision data through robust backend services and surfacing actionable insights via responsive operator dashboards. This role demands someone who can write production-grade Java, run tight Scrum ceremonies, and make sound architectural calls under startup-speed timelines.

Responsibilities:

• Backend Architecture and Hands-on Development: Own the design and development of backend platform built on Java 21+ and Spring Boot 4 x, including RESTful and gRPC APIs, microservices decomposition, event-driven pipelines, and integration layers that connect AI inference engines with factory-floor systems. Architect for scale, reliability, and low latency: design services that handle high-throughput streams from industrial IoT sensors and vision cameras, process them through message brokers (Kafka / RabbitMQ), and persist results across PostgreSQL, MongoDB, Redis, and time-series stores (TimescaleDB / InfluxDB).

Make key technology and design decisions:

• Spring Security and OAuth 2.0 / JWT for multi-tenant authentication, Spring Data for repository abstractions, Spring Cloud for service discovery and configuration, and Hibernate / JPA for ORM while keeping the codebase clean, testable, and well-documented.
• Drive API design standards (OpenAPI / Swagger), enforce contract-first development, and ensure backend services expose well-versioned, idempotent, and backwards-compatible interfaces consumed by the frontend and external integrations.
• Champion production engineering: build observability into every service with structured logging (ELK / Loki), distributed tracing (OpenTelemetry / Jaeger), metrics (Prometheus / Grafana), and alerting; own SLAs and incident response for the backend stack.

Full-Stack Product Delivery:

• Lead end-to-end product builds from the ground up; translate product requirements into technical architecture, break them into epics and stories, and ship complete features spanning backend APIs, database schemas, and frontend UIs.
• Collaborate closely with frontend engineers building operator dashboards and configuration portals (React / Next.js, TypeScript), review UI/UX implementation, ensure performant API integration, and maintain a cohesive full-stack development workflow.
• Own the CI/CD pipeline (GitHub Actions / GitLab CI, Docker, Kubernetes on AWS / Azure / GCP), automate testing (unit, integration, E2E), and enforce quality gates so that every merge to main is production-ready.
• Coordinate with the AI / Data Science teams to integrate ML model outputs (computer vision inferences, LLM responses) into the platform, designing the serving layer, result-caching strategy, and feedback loops that connect model predictions with user-facing features.
• Manage cloud infrastructure decisions across multi-cloud deployments (AWS, Azure, GCP) and on-premises installations at customer factory sites, balancing cost, compliance, and latency requirements.

Team Leadership and Scrum Management:

• Lead, mentor, and grow a cross-functional team of backend and frontend engineers; set clear expectations, conduct regular 1:1s, drive career development, and foster a culture of ownership and technical excellence.
• Run Scrum ceremonies end-to-end: sprint planning, daily stand-ups, backlog grooming, sprint reviews, and retrospectives, ensuring the team delivers predictably while staying agile enough to respond to shifting priorities in a fast-moving start-up.
• Conduct thorough code reviews and architecture reviews; enforce engineering best practices around testing (JUnit, Mockito, Testcontainers), code quality (SonarQube), and secure coding standards.
• Hire and onboard strong engineers; raise the technical bar continuously through pairing, tech talks, design-document culture, and a bias toward building reusable, well-abstracted components.
• Act as the primary engineering interface with Product, Design, AI, Field Engineering, and Customer Success, translating business needs into well-scoped engineering work and communicating trade-offs, timelines, and risks transparently to leadership.

Requirements:

• B. Tech / M. Tech in Computer Science, Software Engineering, or a related discipline.
• 6-10 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.