Our Client is building AI-powered document data infrastructure — turning unstructured documents into structured, queryable databases with deterministic outputs and full audit trails. Their platform ingests, processes, and analyzes complex documents across industries, extracting metadata, identifying key provisions, enabling natural-language search, and delivering real-time AI-assisted insights.
About the Role
We're hiring a Senior Backend Engineer to build and scale our Client's cloud-native microservices platform. You'll work across the full backend stack — from database schema design to cloud infrastructure — shipping features that directly affect how enterprises work with their most important documents.
Working hours: This role operates on GMT (UTC+0) hours to align with distributed team collaboration. For Indonesia-based engineers, this means a shifted schedule.
What You'll Do:
- AI Agent & Chat Systems — Design and extend our real-time AI agent that classifies user queries, orchestrates multi-step search plans, and streams responses via SSE.
- Document Processing Pipelines — Build and improve ingestion, OCR, metadata extraction, clause analysis, and highlighting services.
- LLM Integration — Work with Google Vertex AI (Gemini), implement provider abstraction layers, prompt engineering, classification logic, and fallback strategies.
- Cloud Infrastructure — Provision and manage GCP services (Cloud Run, Pub/Sub, Cloud Build, KMS, Cloud Scheduler) using Terraform
- Database & Data Layer — Design PostgreSQL schemas, write Alembic migrations, implement async repository patterns, and optimize connection pooling.
- CI/CD & Deployment — Maintain and extend Cloud Build pipelines, deployment scripts, traffic management, and rollback procedures.
- Reliability Engineering — Debug production issues, prevent database exhaustion, implement graceful shutdown, stale task recovery, and outbox patterns.
Requirements:
- 7+ years of backend engineering experience — building and operating production systems at scale. Startup or high-ownership environments strongly preferred.
- Deep Python fluency — FastAPI, Pydantic, SQLAlchemy, asyncio. This is a Python-first codebase.
- PostgreSQL — Schema design, migrations (Alembic), query optimization, connection management.
- Google Cloud Platform — Cloud Run, Pub/Sub, Cloud Build, GCS, IAM, KMS. Deep GCP experience is essential — this is not an AWS shop.
- Terraform — Multi-environment infrastructure-as-code for GCP resources.
- Docker — Multi-stage builds, entrypoint scripts, containerized microservices.
- Microservices Architecture — Event-driven systems, task queues, worker patterns, transactional outbox, pub/sub messaging.
- AI/LLM Integration — Practical experience calling LLM APIs, managing prompts, handling streaming responses, and building classification pipelines.
- English Proficiency — Strong written and verbal English for async communication with a distributed team.
Strongly Preferred:
- OCR pipelines (PaddleOCR, Google Vision API, or similar)
- Redis for caching and real-time event delivery
- pgvector / vector search / embeddings
- Feature flag systems (Unleash or similar)
- Legal tech or document processing domain experience
- Bash scripting for deployment automation
