Senior Full Stack Engineer — Java & Kubernetes Focus (Remote)

Senior Full Stack Engineer — Java & Kubernetes Focus (Remote)

Job Summary

Recruitics is looking for a Senior Full Stack Engineer with deep Kubernetes and platform expertise to join our team and help shape the future of recruitment marketing. In this fully remote role, you'll build the platform end to end — from the interfaces companies use to attract and hire top talent, to the APIs, data systems, and container infrastructure that power them. That means working with data that truly matters: data about how people find jobs and how companies reach the right candidates.

This is a full stack role with a serious Kubernetes and data engineering edge and a growing AI focus. You'll own features from the UI all the way down to the pipelines, warehouse, and clusters that run them — and increasingly, the AI and ML capabilities layered on top, from intelligent candidate matching to generative tooling that helps companies write better job content. Kubernetes is central to how we ship and operate everything: our services, data workflows, and AI systems all run on it, and we're looking for someone who's as comfortable designing a deployment, tuning autoscaling, and debugging a networking issue in-cluster as they are shipping a polished frontend or a clean API. The engineers who thrive here are equally comfortable building complete products and operating the platform underneath them.

Our tech stack includes React and TypeScript on the frontend; Kotlin and Spring Boot on the backend; Airflow, DBT, Looker, AWS Redshift, DynamoDB, and MongoDB across our data layer; Kubernetes, Helm, and AWS at the heart of our infrastructure; and a rapidly evolving AI/ML layer built on LLM APIs, embeddings, and vector search. We value autonomy and ownership: you'll have the freedom to innovate and the responsibility to implement solutions independently (with plenty of support from your team). The ideal candidate is a dependable, curious problem solver who isn't afraid to take on complex challenges across the stack — and down into the platform — in a collaborative, egoless environment. Sound like you? Read on!

Responsibilities

In this role you'll work across the full stack, with Kubernetes and data engineering as recurring throughlines. You will:

Own our Kubernetes platform — design, deploy, and operate the services and workloads that run our product. You'll manage cluster configuration, workload manifests and Helm charts, ingress and networking, resource requests/limits and autoscaling (HPA/VPA/cluster autoscaling), rollouts and rollbacks, and the day-to-day reliability of what runs in-cluster. You'll help set the standards for how we package and ship everything on Kubernetes.

Build end-to-end features — design and ship user-facing functionality in React/TypeScript, the backend services behind it (primarily Kotlin and Spring Boot), and the data that powers it. You'll own features from interface to pipeline to the deployment that runs them.

Strengthen our CI/CD and deployment pipelines — build and improve the automation that gets code from commit to cluster safely and quickly, including containerization (Docker), GitOps-style workflows, and progressive delivery. You'll make deploys boring, repeatable, and fast.

Develop and maintain backend services and APIs that process and serve recruitment marketing data to our applications, with an eye toward performance, reliability, and clean contracts between systems — designed to run well as containerized workloads.

Design, build, and optimize data pipelines and workflows to integrate data across Recruitics' analytics platform. (We use tools like Airflow and DBT to orchestrate and transform data, running on Kubernetes.) This is a data engineering edge that sets the role apart — you'll be building applications on top of data you also help shape.

Build AI-powered features — integrate LLMs and ML models into the product to power capabilities like intelligent candidate matching, recommendations, and generative tooling that helps companies craft better recruitment content. You'll work across the full lifecycle: designing prompts and retrieval pipelines, wiring up embeddings and vector search, deploying model-serving workloads on Kubernetes, and shipping these capabilities into real user-facing features.

Manage and tune our data storage systems , including an AWS Redshift data warehouse and NoSQL databases (DynamoDB and MongoDB), to ensure data is organized, high-quality, and performant at scale — and ready to feed our AI/ML systems.

Own observability and reliability across the stack and the cluster — set up metrics, logging, tracing, and alerting (e.g. Prometheus/Grafana or similar); debug issues in application, data, and infrastructure layers; and ensure features and data flow seamlessly from source to destination with minimal downtime. You'll be comfortable diagnosing a failing pod, a noisy neighbor, or a resource-starved node.

Collaborate with cross-functional teams — work closely with product managers, designers, data analysts, and other engineers to understand needs and ensure our products are intuitive, our data is accessible (e.g. powering dashboards in Looker), and our platform serves the whole team well.

Implement best practices for code quality, infrastructure-as-code, data governance, security, and documentation. You'll maintain clear documentation for application, data, and platform workflows, help manage cluster security (RBAC, secrets, network policies), and uphold high standards for integrity and privacy.

Mentor and learn — as a senior member, you'll share your Kubernetes and full-stack knowledge with other engineers, review code and manifests, and contribute ideas to continually improve our engineering and platform practices. (We believe in learning from each other in an egoless team environment.)

Required Experience & Skills

We're looking for a well-rounded engineer who can build complete products and is genuinely strong with Kubernetes and data. The ideal candidate has:

5+ years of experience in software engineering , including senior-level experience designing and building full stack, data-intensive applications.

Strong, hands-on Kubernetes experience (a core requirement for this role) — you've deployed and operated real production workloads on Kubernetes. You're fluent with manifests and Helm, understand networking and ingress, resource management and autoscaling, rollouts, RBAC and secrets, and you know how to debug what's actually happening inside a cluster. Experience with managed Kubernetes (EKS preferred) is a strong plus.

Container and CI/CD proficiency — solid experience with Docker and with building automated pipelines that ship containerized workloads (GitOps, progressive delivery, or similar). Familiarity with infrastructure-as-code (Terraform or similar) is valuable.

Full stack proficiency — hands-on experience building frontends (ideally React/TypeScript or a similar modern framework) and backend services. You're comfortable owning a feature across the whole stack rather than just one layer.

Backend depth on the JVM — required — strong, professional experience with Java and the JVM is a must for this role. Kotlin experience is highly desirable (it's our primary backend language), and production experience with Spring Boot is expected. Python for data processing is a welcome addition.

Data engineering chops — you've built or maintained ETL workflows using tools like Apache Ai