Back-end Software Engineer
Back-end Software Engineer
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1 Vacancy
Job Description
This is a remote position.
About the Role:
You ll thrive here if you re an autonomous problem solver who optimizes systems for speed reliability and cost someone who thinks in automation and ships measurable results fast.
Responsibilities:
Design and maintain APIs for AI-powered features (FastAPI Flask)
Integrate and fine-tune LLMs (OpenAI Hugging Face LangChain)
Build pipelines for vector embeddings semantic search and RAG
Optimize back-end systems for latency scalability and cost
Collaborate with ML engineers to deploy and monitor inference systems
Implement observability (Sentry Prometheus Grafana) for debugging
Manage CI/CD and infrastructure-as-code (Docker GitHub Actions Terraform)
Own full product verticals from API to deployment
Requirements:
3 years in back-end/API engineering (Python FastAPI/Flask)
Experience with PostgreSQL Docker and containerized development
Proven use of OpenAI APIs Hugging Face LangChain or Transformers
Familiar with vector databases like Pinecone Qdrant or Weaviate
Experience in CI/CD observability and monitoring systems
Bonus: Knowledge of asyncio aiohttp k8s or serverless environments
Strong communication async-first documentation and remote collaboration skills
Set up staging and dev environments
Review codebase and system architecture
Deploy test API integrating a basic OpenAI or HF model
By Day 60
Launch a production-ready AI feature (e.g. vector store or RAG endpoint)
Improve model response latency by 30 50%
Implement >80% test coverage
By Day 90
Own back-end infrastructure for a product line
Reduce compute costs through caching/async strategies
Contribute to LLM scaling roadmap
Success Metrics (KPOs):
API latency < 500ms on average
Uptime 99.5% on core services
Test coverage > 85%
1 2 production deployments per week
LLM inference 3s with retries/failure handling
Tech Stack:
AI Platforms: OpenAI Hugging Face LangChain
Frameworks: FastAPI Flask SQLAlchemy
Databases: PostgreSQL Redis Pinecone Qdrant
DevOps: Docker GitHub Actions Terraform
Monitoring: Prometheus Grafana Sentry
Collaboration: Slack Notion ChatGPT
RESPONSIBILITIES & DUTIES Architect and maintain APIs that serve AI/LLM-powered services with sub-second latency Deploy, fine-tune, and manage OpenAI, Hugging Face, or open-source models for live use cases Build scalable pipelines for vector embeddings, semantic search, and retrieval-augmented generation (RAG) Implement observability (logging, metrics, tracing) to support real-time debugging and performance insights Optimize infrastructure performance via caching layers, async frameworks, or resource scaling Design and maintain DevOps workflows for CI/CD, infrastructure-as-code, and production deployments Collaborate cross-functionally with ML engineers, product owners, and designers to ship and scale features Continuously document architecture, workflows, and improvement initiatives in async-first platforms REQUIREMENTS 3+ years in back-end/API development with a focus on performance and reliability Advanced Python experience with FastAPI or Flask Strong in PostgreSQL and Docker-based development environments Proven use of OpenAI APIs, Hugging Face Transformers, or LangChain in real-world apps Familiar with vector databases (e.g., Pinecone, Qdrant, Weaviate) Hands-on experience in CI/CD pipelines using GitHub Actions, Terraform, or similar Comfortable building in async environments using asyncio, aiohttp, or equivalents Clear, documented, and self-driven: able to work independently in remote, async environments
Employment Type
Full Time
