Senior Backend / Platform Engineer

This is a hands-on R&D role for a Senior Backend/Platform Engineer to build and optimize a Python backend for a radar system that detects and tracks small drones. You will own the core signal-detection pipeline, working on real-time data ingestion, AI integration, and infrastructure, with direct impact on product capabilities.

Responsibilities

• Pipeline — Build a Python backend that ingests a live I/Q stream and manages queues, buffers, processes and data flow.
• Real-time path — Move large I/Q matrices into the AI core with minimal latency using shared memory, zero-copy and ring / ping-pong buffers — not REST.
• Integration — Wrap and profile the team's math/AI modules (NumPy, ONNX Runtime / PyTorch) and remove bottlenecks together with the signal engineers.
• Data layer — Design the schema for tracks, events and metadata; async writes via asyncpg / SQLAlchemy async. Raw I/Q stays in RAM; raw logs go to cold storage.
• API & UI — FastAPI for commands, auth and status; secure WebSockets streaming tracks to a simple operator dashboard (Plotly Dash / Streamlit).
• Infra — Docker / Docker Compose, GitHub Actions CI/CD, shared-memory config in containers, Terraform-ready deployment.
• Security — TLS to Postgres, HTTPS/WSS, JWT auth, network isolation, secrets handling, least-privilege access.

Requirements

• Senior (or strong mid) Python engineer who has built real engineering systems, not only web APIs.
• Solid with asyncio, multiprocessing and multiprocessing.shared_memory.
• Comfortable with large data matrices (NumPy) and profiling / optimising Python for latency and throughput.
• PostgreSQL (asyncpg or SQLAlchemy async), FastAPI, REST, WebSockets.
• Docker, Docker Compose, Linux, Git / GitHub Actions.
• Security basics: TLS, HTTPS, WSS, JWT.

Nice to have

• ONNX Runtime / PyTorch inference, CuPy, Numba, SciPy, GPU inference.
• ZeroMQ / PyZMQ, Zarr / HDF5, structured logging, Prometheus / Grafana.
• Linux performance tuning (CPU affinity, taskset, psutil), Terraform, Ansible.
• Any exposure to high-throughput / low-latency systems, SDR, radar, signal processing, streaming or telemetry pipelines.

Benefits

• Impact
• Own the core signal-detection system. Your work directly shapes what the product can detect, understand, and act on.
• Engineering Challenges Worth Solving
• Work on complex radar, DSP, and signal-processing problems that are typically found only in large R&D organizations or deep-tech companies. You'll tackle hard technical challenges with direct influence on outcomes.
• A Team You'll Learn From
• Collaborate closely with scientists, engineers, and operators who combine deep technical expertise with a strong product mindset. No layers of bureaucracy—just smart people solving meaningful problems together.
• Ownership & Autonomy
• We're looking for builders, not executors. You'll have the freedom to make decisions, take responsibility, and drive critical parts of the technology forward.