Weekday AI
SeniorBackendEngineer
“Senior Backend Engineer at Weekday AI. Skills: Python, FastAPI, RESTful APIs, microservices architecture, Large Language Models (LLMs), PostgreSQL, MongoDB, Redis. build and scale intelligent backend systems powering AI-driven applications. designing robust APIs”
What You'll Achieve.
high performance; reliability; scalability; efficient, production-ready solutions; high-performance applications; optimize intelligent features in production; efficient data handling; system reliability; performance optimization; scalability across services
Industry & Context.
problem-solving and debugging skills
What They're Looking For.
Must Have
5–9 years of backend development experience, proficiency in Python, Hands-on experience with FastAPI or similar frameworks (Flask/Django), Practical experience working with Large Language Models (LLMs) and AI-driven systems, knowledge of REST APIs, microservices architecture, and distributed systems, Experience with databases like PostgreSQL, MongoDB, and Redis, problem-solving and debugging skills, Ability to design scalable, maintainable, and high-performance backend systems
Nice to Have
Understanding of agentic AI concepts or autonomous workflows, Familiarity with cloud platforms such as AWS, GCP, or Azure, Effective communication and collaboration skills in cross-functional environments
What You'll Do.
build and scale intelligent backend systems powering AI-driven applications
designing robust APIs
developing scalable microservices
integrating advanced AI capabilities such as Large Language Models (LLMs) and agentic workflows into production environments
shaping backend architecture
enabling seamless communication between systems
ensuring high performance
translate complex requirements into efficient
production-ready solutions
Design and develop scalable backend systems using Python and modern frameworks like FastAPI
Build and maintain RESTful APIs and microservices architecture for high-performance applications
Integrate and operationalize LLMs and agentic AI workflows into backend systems
Collaborate with AI/ML teams to deploy and optimize intelligent features in production
Work with databases such as PostgreSQL
and Redis for efficient data handling
Ensure system reliability
performance optimization
and scalability across services
Contribute to architectural decisions and evaluate trade-offs for backend design
Collaborate with cross-functional teams to deliver end-to-end product features
and resolve complex production issues
Follow best practices in code quality
How You'll Work.
Team & Collaboration
Working closely with product, AI, and engineering teams; Collaborate with AI/ML teams; Collaborate with cross-functional teams
Communication Scope
Effective communication and collaboration skills in cross-functional environments
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