Senior Software Engineer - GrowthOS Platform

Overview

Senior Software Engineer - GrowthOS Platform

Location: Remote / Hybrid
Type: Full-time
Team: Core Platform Engineering

About Intempt GrowthOS

GrowthOS is Intempt’s autonomous growth platform for Product-Led Growth (PLG) companies. It operates at billion-scale event volumes, powers real-time personalization and journeys, and embeds decisioning models (NBA, uplift, experimentation) directly into product and marketing workflows.

This is not a CRUD SaaS. GrowthOS is a distributed, real-time decision system built on streaming data, low-latency inference, and multi-tenant isolation. Engineers here work on systems that directly affect how millions of users are segmented, personalized, and activated in real time.

Role Overview

As a Senior Software Engineer, you will design, build, and operate core GrowthOS services. You will work on high-throughput data pipelines, real-time APIs, decisioning engines, and platform primitives that other teams (Journeys, Personalization, Experiments, Enrichment) build on top of.

This role is hands-on, system-level, and performance-oriented. You will own production systems, influence architecture, and set engineering standards.

What You Will Build

Core Platform Systems

• Real-time ingestion and processing of user events (Kafka → Flink → ClickHouse)

• Low-latency APIs for:

  • User & Account resolution
  • Segmentation and audience evaluation
  • Journey and personalization execution
  • Next Best Action (NBA) inference

• Multi-tenant data isolation at scale (Org → Project → User model)

Decisioning & Intelligence Infrastructure

• Real-time NBA and uplift inference services (no LLM shortcuts)

• Hybrid retrieval systems using:

  • ClickHouse for factual/analytical lookups
  • Qdrant for semantic/vector retrieval

• Model-agnostic inference pipelines (batch + real-time)

• Feature generation from structured objects (User, Account, Events, Segments)

Data & Streaming

• Kafka-backed event pipelines with strict ordering and idempotency
• Flink jobs for sessionization, enrichment, and stateful computation

• ClickHouse schemas optimized for:

  • High-cardinality user data
  • Fast segment evaluation
  • Time-series behavioral analysis

• Redis for low-latency caching and real-time state

Platform Reliability & Scale

• Services that handle:

  • Millions of events per second
  • Tens of millions of users
  • Thousands of concurrent tenant workloads

• Backpressure handling, retries, DLQs, and replayability

• Explicit performance budgets and SLOs

Technologies You Will Use (Daily)

Languages

• Java (core services, streaming, APIs)
• Python (model training, batch jobs, inference services)

Data & Infrastructure

• Kafka — event streaming backbone
• Flink — stateful stream processing
• ClickHouse — primary analytical & user data store
• PostgreSQL — configuration, metadata, control plane
• Redis — caching, fast lookups, real-time state
• Qdrant — vector storage and semantic retrieval

Platform & Deployment

• Kubernetes (EKS) — fully self-managed
• Helm + Terraform — infra and service deployment
• ArgoCD — GitOps delivery
• vLLM / TorchServe — model inference (where applicable)

Observability & Quality

• Self-managed observability stack
• SonarCloud for code quality and DX metrics
• Strict code review and definition-of-done standards
• Load testing for real-time pipelines

Responsibilities

Engineering Execution

• Design and implement backend services with clear ownership
• Write production-grade code with explicit performance characteristics
• Review code with a focus on correctness, scalability, and maintainability
• Debug distributed systems issues across Kafka, Flink, and microservices

Architecture & Systems Thinking

• Make informed tradeoffs between latency, cost, and complexity
• Design schemas and APIs that survive real-world scale
• Prevent over-engineering while avoiding shortcuts that break at scale
• Push back on vague requirements — demand clarity and measurable outcomes

Operational Ownership

• Own services in production (build it, run it)
• Participate in incident analysis and postmortems
• Improve reliability through design, not heroics
• Enforce cost-aware engineering (infra changes require justification)

What We Expect From You

Required

• 6+ years of backend engineering experience

• Strong fundamentals in:

  • Distributed systems
  • Data modeling
  • Concurrency and performance

• Proven experience operating production systems at scale

• Deep experience with Java or Python (ideally both)

• Comfort working directly with Kafka-based architectures

• Ability to reason about system behavior under load

Strongly Preferred

• Experience with ClickHouse or similar columnar OLAP stores
• Stream processing with Flink or equivalent
• Designing real-time APIs with strict latency requirements
• Multi-tenant SaaS architecture
• ML-adjacent systems (feature pipelines, inference APIs), even if not a data scientist

What This Is Not

• Not a frontend role
• Not a “just ship features” role
• Not a low-ownership environment
• Not an LLM-toy startup

This role is for engineers who care about systems that work, scale that’s real, and decisions backed by data, not vibes.

Why This Role Matters

GrowthOS is the foundation for everything Intempt ships. If the platform is slow, wrong, or unreliable, nothing else matters. Senior engineers here directly shape the product, the architecture, and the company’s technical direction.

You will have leverage, ownership, and real impact — not just tickets.