About the Role
The role involves developing robust backend infrastructure for AI applications, with a focus on large language models and intelligent agent systems, ensuring high performance, scalability, and seamless integration.
Responsibilities
- Design and implement scalable backend services for AI-powered applications
- Develop and optimize APIs that support LLM integrations
- Build and maintain systems that orchestrate AI agent behaviors
- Ensure data flow efficiency between machine learning models and backend services
- Collaborate with data scientists to productionize AI models
- Monitor system performance and troubleshoot backend issues
- Improve reliability and fault tolerance of distributed services
- Write clean, maintainable, and well-documented code
- Integrate authentication and authorization mechanisms for secure access
- Support deployment pipelines and CI/CD workflows
- Optimize database queries and storage solutions for AI workloads
- Participate in architectural design and technical planning
- Ensure compliance with data privacy standards
- Contribute to technical documentation and system diagrams
- Evaluate new technologies for backend enhancements
- Work closely with frontend teams for seamless feature delivery
- Implement logging and monitoring for backend components
- Manage version control and code reviews
- Scale infrastructure to meet growing AI processing demands
- Maintain uptime and responsiveness of critical services
- Refactor legacy systems to support modern AI frameworks
- Assist in defining best practices for backend development
- Support testing strategies including unit and integration tests
- Respond to incidents and perform root cause analysis
- Stay current with advancements in AI and backend technologies
Nice to Have
- Master’s degree in computer science or AI-related discipline
- Experience with transformer-based models
- Contributions to open-source AI projects
- Familiarity with LangChain or similar frameworks
- Experience with vector databases like Pinecone or Weaviate
- Background in natural language processing
- Knowledge of reinforcement learning concepts
- Experience with serverless architectures
- Exposure to MLOps practices
- Published research or papers in AI fields
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible remote options
Team
Collaborative engineering team focused on AI innovation
Tech Stack
- Primary language: Python
- Frameworks: FastAPI, Flask, Django
- Cloud: AWS, GCP
- Containerization: Docker, Kubernetes
- Databases: PostgreSQL, MongoDB, Redis
- AI tools: Hugging Face, LangChain, LlamaIndex
- Monitoring: Prometheus, Grafana
- CI/CD: GitHub Actions, Jenkins
What We Offer
- Opportunity to work on cutting-edge AI technologies
- Flexible working hours and remote options
- Professional development budget
- Health and wellness benefits
- Team retreats and social events
- Stock options for eligible employees
- Modern office space with ergonomic setups
- Supportive and inclusive work culture
Available for qualified candidates
