Backend Engineer (Python — Django/FastAPI) · AWS · Mid-Level

We’re hiring a hands-on Backend Engineer (approx. 3–5 years) to own core services in a cloud-native platform that ingests IoT events (IP cameras, access control, sensors) and processes them in real time. You’ll collaborate closely with the Head of R&D on architecture, delivery, and quality.

We also ship AI features (GenAI and other ML/CV). If you bring prior AI/GenAI integration experience, that’s a strong advantage—but the core of the role is backend engineering.

What you’ll do

• Build and maintain Python microservices (Django/FastAPI) and robust REST APIs.
• Design scalable data flows and ingestion for IoT events; add real-time endpoints (WebSockets) where it makes sense.
• Help shape architecture, standards, and technical decisions; break down work and estimate sensibly.
• Deploy and operate services on AWS; containerize with Docker (Kubernetes is a plus).
• Work with PostgreSQL, Redis, RabbitMQ; add logs/metrics; debug performance and reliability issues.
• If relevant to your background: contribute to AI features (e.g., embeddings/RAG endpoints, prompt orchestration) and productionize external AI API integrations.

Must-have

• 3–5 years building production backends in Python with Django and/or FastAPI.
• Production API experience: authentication (JWT/OAuth2), pagination, versioning, idempotency; basic rate limiting.
• Strong with PostgreSQL (schema design, indexing, efficient queries) and Redis (caching + invalidation).
• Docker and CI/CD with Git; deployed at least one service to AWS (EC2/ECS/EKS, S3, or RDS).
• Events & messaging: RabbitMQ (or similar), retries/backoff, idempotent consumers.
• Realtime basics: WebSockets or similar tech.
• Testing and ops awareness: pytest, meaningful logging/metrics (Sentry/Prometheus/Grafana), secure config/secrets.
• Clear communication, ownership, and a bias to action in a small team.

Nice to have

• GenAI/ML integrations (OpenAI/Anthropic/Hugging Face), embeddings/RAG, vector DBs (OpenSearch k-NN, Pinecone, Qdrant), prompt design/evaluation/guardrails.
• Kubernetes (EKS), Terraform/Helm; IoT/video (RTSP, webhooks).
• Tracing/observability (Loki/Jaeger), performance profiling.
• Light frontend (Vue/JS) for internal tools.
• Education/Certs: BSc in Computer Science/Software Engineering or equivalent practical experience; AWS certs are a plus (not required).

Our stack

Python (Django/FastAPI, DRF) · PostgreSQL · Redis · RabbitMQ (Amazon MQ) · Docker · Kubernetes (EKS) · AWS (EC2/ECR/EKS/S3/CloudFront/RDS/ElastiCache) · OpenSearch · Sentry · Prometheus/Grafana/Loki

(AI where relevant: OpenAI/HF + vector DBs)

Why join us

• Build meaningful cloud + IoT features with real ownership and quick decisions.
• Small, supportive team; direct collaboration with the Head of R&D.
• Modern stack, practical engineering, low bureaucracy.
• Hybrid work (~1 day WFH/week). Clear path to broaden responsibility over time.

Hiring process (fast and candidate-friendly)

2–3 short steps, total live time ≤90 min. Quick feedback within 3–5 business days.