Senior Platform Engineer (Java & Python)
Intempt processes 350M+ events/month across a unified Customer Data Platform, analytics, and ML stack. The core works. We need someone to make it bulletproof at scale.
You'll own the infrastructure that powers real-time personalization, journeys, and decisioning models. Java for the platform services, Python for the ML and data pipelines. This is platform engineering - not application development.
What you'll own
- High-throughput event ingestion and stream processing (Kafka, Flink)
- Low-latency query paths across ClickHouse, Postgres, and Neo4j
- JVM performance - GC tuning, heap profiling, hot path optimization
- Infrastructure stability under real load - not theoretical load
- Python data pipelines - ML serving, embedding jobs, batch processing
- System reliability, observability, and incident response
You are
- 5+ years deep in Java and Python backend systems - not just Spring CRUD, actual platform work
- Someone who has personally tuned a pipeline processing millions of events per hour
- Comfortable with distributed systems failure modes - partitions, back-pressure, replication lag
- The person who finds the bottleneck before the pager does
Stack you'll live in
Java 21PythonSpring Boot WebFluxFastAPIKafkaApache FlinkClickHousePostgreSQLNeo4jRedisKubernetesAWSNot a fit if
- You need clean requirements to get started
- You think "it works at small scale" closes a ticket
5+ years deep experience in Java and Python backend systems, including platform work, distributed systems, and performance tuning.
Key Responsibilities
- owning infrastructure
- optimizing performance
- ensuring reliability
Skills & Tools
Java 21, Python, Spring Boot WebFlux, FastAPI, Kafka, Apache Flink, ClickHouse, PostgreSQL, Neo4j, Redis, Kubernetes, AWS
Job Details
- Category: Software Development
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About Intempt
A company processing 350M+ events per month across a unified customer data platform, analytics, and ML stack. — Industry: Information Technology