5 years of overall experience in software development.
3 years of professional experience focusing on Python microservices architecture.
2 years hands-on experience with asynchronous frameworks like FastAPI or aiohttp.
Strong proficiency in SQL and NoSQL databases, including ORMs like SQLAlchemy.
Familiarity with cloud platforms like AWS, Azure, or GCP.
Solid understanding of distributed systems design patterns.
Experience in domains like Chat, IVR, or Banking is a plus.
Responsibilities
Design and optimize generative AI models using tools like TensorFlow or PyTorch.
Develop efficient microservices in Python with frameworks like FastAPI or Flask.
Build and maintain RESTful APIs and GraphQL endpoints.
Manage relational and NoSQL databases with a focus on data consistency.
Implement event-driven architecture with tools like Kafka or RabbitMQ.
Containerize applications using Docker and orchestrate with Kubernetes.
Write comprehensive tests and set up monitoring tools for service health.
Benefits
Health, dental, and vision insurance.
401(k) plan with company match.
Flexible work hours and remote work options.
Professional development opportunities.
Paid time off and holidays.
Full Job Description
Req ID: 376261
Job Description:
Design, implement, and optimize generative AI models using frameworks like TensorFlow, PyTorch, or JAX, including architectures like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Large Language Models (LLMs).
Design and deploy efficient, self-contained microservices using Python 3.x and modern web frameworks (FastAPI, Flask, or Django).
Build and maintain RESTful APIs and GraphQL endpoints for seamless communication between services and front-end applications.
Work with both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases. Implement database-per-service patterns and ensure data consistency.
Implement message queues and event-driven architecture using Kafka, RabbitMQ, or Celery.
Containerize microservices using Docker and orchestrate them utilizing Kubernetes.
Write comprehensive unit and integration tests. Configure logging and monitoring tools (Prometheus, Grafana, ELK stack) to track service health.
Select appropriate datasets and data representation methods.
Extend existing machine learning libraries and frameworks.
Train systems and retrain as necessary.
Skills Required:
Overall 5 years of experience.
3 years of professional software engineering experience, with a heavy focus on Python-based microservices architecture.
2 years of hands-on experience with asynchronous Python frameworks like FastAPI or aiohttp.
Strong proficiency in SQL/NoSQL integration, including ORMs like SQLAlchemy.
Familiarity with cloud environments (AWS, Azure, or GCP) and infrastructure-as-code principles.
Solid understanding of distributed system design patterns (e.g., CQRS, Event Sourcing, Circuit Breakers).
Experience with Chat, IVR, Banking will be a plus.
