Backend / Platform Developer Consultant (Temporal & Kubernetes)

PLEASE NOTE: At this time, we are only considering candidates located in and authorized to work in the United States.

JOIN OUR TEAM!

Bitovi is looking for a Backend / Platform Developer Consultant to join us as we transform technology delivery. We build and operate durable, distributed systems for enterprise clients — heavy on Java Services, Temporal for workflow orchestration, Kafka for event streaming, and Kubernetes-native platform engineering on AWS to run it all reliably. If you want to build exceptional systems, take orchestration, systems engineering, and infrastructure seriously, and have ideas on how to make delivery more collaborative, validation-driven, and swift, we want to work with you!

WHO YOU ARE

You’re experienced building and running applications at the enterprise level, and you’re comfortable owning both the code and the infrastructure it runs on. You think like a systems engineer — reasoning about the whole platform, from JVM services and event streams to the clusters and cloud infrastructure underneath them. You thrive when given opportunities to deliver real-world platforms as an integral team member, including large-scale migrations, and you have the expertise to interface and communicate confidently with stakeholders.

You’ll excel in this role at Bitovi if you have:

• Strong working knowledge of Java and the JVM ecosystem (Spring Boot or similar); experience with additional backend languages (Go, Python, TypeScript/JavaScript, C#, etc.) is a plus
• Hands-on experience with a durable execution / workflow engine — Temporal preferred (Apache Airflow, Prefect, or similar also relevant) — including modeling workflows and activities, handling retries and timeouts, and reasoning about idempotency and failure modes
• Experience designing and operating Kafka-based event streaming systems: topic and partition design, consumer groups, schema management, and reasoning about ordering, delivery guarantees, and consumer lag
• Experience designing and building GraphQL APIs — schema design, resolvers, and performance concerns (N+1, caching, pagination); federation experience a plus
• Deep, hands-on AWS experience: architecting, deploying, and operating production systems (EKS, networking, IAM, messaging, and data services)
• Solid Kubernetes experience: deploying, operating, and debugging production workloads
• A systems engineering mindset: understanding of complex scaling issues, concurrency, backpressure, caching strategies, and failure modes across distributed systems
• Experience planning and executing migrations — application replatforming, workflow engine migrations, data/schema migrations, or moving workloads between environments with minimal downtime
• A thorough understanding of CI/CD pipelines and GitOps-style delivery
• Experience with observability in practice — logging, metrics, and tracing (OpenTelemetry a plus)
• Experience building modern microservice-based or serverless applications
• Database schema design and development expertise

Other skills we value

Temporal depth

• Running Temporal in production — self-hosted on Kubernetes and/or Temporal Cloud
• Workflow versioning and patching, safe deployments, and long-running workflow migrations
• Worker deployment and tuning (pollers, task queues, concurrency/slot configuration)
• Namespace management, mTLS (SPIFFE/SPIRE or private CA), and capacity/scaling concerns (e.g. APS/TRU on Temporal Cloud

Kafka & event streaming depth

• Operating Kafka in production (MSK, Confluent, or self-managed on Kubernetes)
• Kafka Connect, Kafka Streams, and schema registry workflows (Avro/Protobuf)
• Migrating between clusters or providers, and integrating Kafka with downstream analytical stores
• Experience with different techniques for processing large datasets, such as Lambda and Kappa architectures

Platform / DevOps depth

• Building or operating an internal developer platform (IDP) — self-service, paved-path infrastructure for application teams
• GitOps with ArgoCD (or Flux) and a low- or zero-manual-apply delivery model
• Infrastructure as code: Terraform/OpenTofu, and provisioning AWS resources via Crossplane, ACK, or similar
• Writing Kubernetes controllers/operators (controller-runtime, kubebuilder) and working with CRDs
• Helm chart authoring and distribution (including OCI/registry-based)
• Secrets management (External Secrets Operator, etc.), autoscaling (Karpenter, KEDA), and service mesh concepts (Istio, SPIFFE/SPIRE) …