Metric Tree Labs
Website:
metrictreelabs.com
Job details:
Senior Full Stack Python Developer
Experience: 5+ Years
About the Role
We are looking for a Senior Full Stack Python Developer who combines strong backend engineering with hands-on DevOps and modern AI/ML capabilities. You will take end-to-end ownership of product features — from architecture to deployment — in a fast-moving, high-ownership environment with direct access to founding leadership.
Key Responsibilities
- Design and build scalable backend services and REST/GraphQL APIs using Python (FastAPI / Django / Flask)
- Develop responsive frontend interfaces using React.js or Vue.js
- Own CI/CD pipelines and infrastructure-as-code using Docker, Kubernetes, Terraform, and GitHub Actions
- Manage and optimize cloud infrastructure on AWS / GCP / Azure — serverless, containers, and managed databases
- Integrate LLM and AI/ML APIs (OpenAI, Anthropic Claude, Hugging Face) into production workflows
- Design and maintain data stores — PostgreSQL, MongoDB, Redis, and vector databases
- Implement observability and alerting using Prometheus, Grafana, or Datadog
- Conduct code reviews and establish engineering best practices
Required Skills
Backend
- Python 3.x — FastAPI, Django REST Framework, or Flask
- REST APIs, GraphQL, microservices, event-driven architecture
- Message brokers: Kafka, RabbitMQ, or AWS SQS
- Testing: Pytest (unit, integration, e2e)
Frontend
- React.js (hooks, Redux, context) or Vue.js
- TypeScript, HTML5, CSS3, Vite / Webpack
DevOps & Cloud
- Docker, Kubernetes, Helm
- CI/CD: GitHub Actions, GitLab CI, or Jenkins
- Infrastructure as Code: Terraform or AWS CDK
- AWS (Lambda, ECS, RDS, S3, CloudFront) or GCP / Azure equivalent
- Linux, bash scripting, IAM, secrets management
AI / ML
- LLM API integrations — OpenAI, Anthropic, Gemini
- RAG pipelines, vector databases (Pinecone, pgvector, Weaviate)
- Prompt engineering and AI cost optimization
- Familiarity with PyTorch, TensorFlow, or scikit-learn
Databases
- PostgreSQL / MySQL — schema design, query optimization
- MongoDB, DynamoDB
- Redis for caching and sessions
Qualifications
- 5+ years of professional software development, with 3+ years in Python backend
- Proven production experience with DevOps toolchains and cloud infrastructure
- Demonstrable experience integrating AI/ML in production environments
- Strong communication and ability to document architecture decisions
- B.Tech / M.Tech / B.Sc in Computer Science or equivalent practical experience
Nice to Have
- Early-stage startup or founder-adjacent experience
- AWS / GCP / Azure certifications
- Open-source contributions
- Familiarity with data engineering tools (Airflow, dbt)
Click on Apply to know more.