Engineering Manager

The candidate will have responsibilities across the following functions:

Backend Architecture and Hands-on Development:

• Own the design and development of Ripik's 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 to 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 Ripik's 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.
• 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.