We are looking for a Senior Python Backend Engineer to join a high-impact team working on a complex, data-intensive platform. This role focuses on building and scaling backend services that support large-scale data processing, search, and event-driven architectures.
You’ll work in a modern cloud-native environment, collaborating with cross-functional teams to design, develop, and optimize distributed systems. This is an excellent opportunity for engineers who enjoy working with high-throughput systems, search technologies, and real-time data pipelines.
Responsibilities
Design, develop, and maintain scalable backend services using Python (3.10–3.12) and Flask
Build and optimize RESTful APIs using tools such as Flask-RESTX and Flask-SQLAlchemy
Work with PostgreSQL for schema design, query optimization, and database migrations (Alembic)
Develop and maintain integrations with Elasticsearch for indexing, querying, and large-scale search capabilities
Implement and manage event-driven architectures using Apache Kafka
Deploy and manage containerized applications using Docker and Kubernetes (EKS)
Collaborate on infrastructure and deployment workflows using Helm and Argo CD (GitOps)
Monitor and troubleshoot systems using Datadog and SentryContribute to system performance tuning, scalability improvements, and reliability initiatives
Collaborate with cross-functional teams including frontend, data, and ML engineer
Required Skills
Strong experience with Python backend development (Flask preferred)
Solid understanding of SQLAlchemy and Alembic for ORM and migrations
Hands-on experience with PostgreSQL (schema design, performance tuning)
Experience working with Elasticsearch (querying, indexing, cluster concepts)
Knowledge of Apache Kafka and event-driven systems (consumer/producer patterns)
Experience with containerization (Docker) and Kubernetes (debugging pods, logs, deployments)
Familiarity with AWS services such as S3, EC2, and EKS
Strong problem-solving skills and ability to work in distributed systems environments
Nice to Have
Experience with Redis for caching or task queues
Exposure to machine learning or NLP pipelines
Familiarity with libraries such as PyTorch, HuggingFace Transformers, spaCy, or scikit-learn
Experience working with GPU/CUDA-based workloads
Frontend exposure with React and TypeScript
Experience with LangChain, OpenAI APIs, or similar AI tools
Technical Environment
Backend:
Python, Flask, Gunicorn (gevent)
Databases:
PostgreSQL, Elasticsearch, Redis
Streaming:
Apache Kafka
Cloud & DevOps:
AWS (EKS, S3, EC2), Docker, Helm, Argo CD
Observability:
Datadog, Sentry
Frontend:
React, TypeScript, Redux, Vite, Mapbox GL