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,