AI Platform Engineer

We are now expanding our team and are looking for skilled, goal-oriented backend developers to join our platform and custom solution teams.

Our stack

• Python 3.12+ and NodeJS as our core languages – Python for rapid development, NodeJS for telephony integrations and high-performance components.

• Cloud-native infrastructure: Kubernetes orchestration with Helm, multi-cloud deployment across AWS.

• GCP, and AzuregRPC, REST APIs, WebSockets and Kafka for service communication.

• GitHub Actions for CI/CD, Docker for containerization, with Grafana, Prometheus, and OpenTelemetry for observability.

• PostgreSQL, ClickHouse for analytics, and specialized vector databases for AI workloads.

Responsibilities

• Architect high-performance real-time systems: Design micro-services and streaming architectures that handle millions of concurrent voice/text AI interactions with ultra-low latency.

• Create foundational platform components: Build reusable infrastructure blocks (rate limiters, service mesh, circuit breakers), developer tools (APIs, SDKs), and observability solutions that enable teams to ship AI features rapidly.

• Optimize AI infrastructure end-to-end: Manage GPU clusters, design model serving pipelines, implement vector similarity search, and collaborate with ML engineers to ensure efficient model deployment and inference.

• Enable engineering excellence: Establish platform standards, deployment patterns, and self-service automation that empower product teams to move fast while maintaining reliability.

Requirements

• Pragmatic engineering approach: Balance speed and quality by shipping working solutions quickly when needed, while keeping code clear and maintainable over clever abstractions.

• Strong programming skills in Python (expert level with type systems and modern ecosystem) and Go (for performance-critical components).

• Production-scale distributed systems experience: Building and operating micro-services architectures with service discovery, API gateways, event-driven patterns, and proven ability to handle large-scale production workloads.

• Real-time systems and observability expertise: Experience with streaming architectures, message queues, low-latency optimization, plus deep knowledge of distributed tracing, metrics aggregation, and log analysis at scale.

• Strategic thinking: For critical architectural decisions, you invest time to evaluate multiple approaches, present top candidates with trade-offs, and document why alternatives were rejected.

• Outstanding technical communication: Ability to clearly explain complex architectural decisions, write comprehensive documentation, facilitate productive technical discussions, and effectively communicate with both engineering teams and stakeholders.

What we offer?

• High-impact projects with prominent clients and our proprietary AI platform development.

• Cutting-edge technology stack with the latest tools in AI infrastructure and platform engineering.

• Budgets for the latest AI models (GPT-4, Claude, etc.) to ensure our team has the best tools available.

• Rapid career progression working alongside senior professionals from leading tech companies.

• Remote work flexibility from Europe.

• Direct influence on platform architecture decisions that shape our AI products.