Backend / Platform Developer Consultant (Temporal & Kubernetes)

Bitovi•Chicago, IL

19d•Remote

About The Position

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! 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) EKS or comparable managed Kubernetes at scale General Interest in working across multiple backend languages Additional queueing and messaging technologies (AWS SQS/SNS, RabbitMQ) API design across paradigms (GraphQL, REST, gRPC) AuthN/AuthZ and related technologies (sessions, API tokens, JWTs) Automated testing across the stack (unit, integration, performance/benchmarking)

Requirements

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

Nice To Haves

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)
EKS or comparable managed Kubernetes at scale
Interest in working across multiple backend languages
Additional queueing and messaging technologies (AWS SQS/SNS, RabbitMQ)
API design across paradigms (GraphQL, REST, gRPC)
AuthN/AuthZ and related technologies (sessions, API tokens, JWTs)
Automated testing across the stack (unit, integration, performance/benchmarking)

Responsibilities

Build durable systems. Design and implement Java services, Temporal workflows, and Kafka-based event pipelines, and help clients adopt durable execution and event streaming the right way — from first workflow to production scale.
Lead modernization efforts. Plan and execute large-scale modernization efforts — moving workflows, services, and data between platforms, clusters, and clouds — with safety, observability, and minimal disruption as first-class requirements.
Own the platform. Build and operate Kubernetes-native infrastructure and CI/CD on AWS so application teams can ship safely and quickly. Treat reliability, observability, and repeatability as part of the deliverable, not an afterthought.
Consult and manage. Consult with clients to build outcome-driven applications and platforms, guiding them through the process, identifying potential problems and unknowns, and tackling challenges.
Travel. This is a remote, full-time position that requires the ability to travel. We travel an average of 3–5 days every quarter, and we'll always do our best to work with your schedule.
Teach. We'll discuss opportunities for you to present at conferences, attend and give training, plan and run meetups or local groups, and create various kinds of content in your expertise.