About the Role
This position involves designing and implementing fullstack solutions where AI is integrated at the core of the architecture, requiring strong skills in both frontend and backend development, along with experience in real-time data processing and scalable infrastructure.
Responsibilities
- Develop and maintain fullstack applications with AI components embedded throughout
- Design user interfaces that reflect intelligent, data-driven behaviors
- Build backend services that support machine learning workflows and real-time inference
- Collaborate with data scientists to integrate models into production systems
- Optimize application performance for low-latency, high-throughput environments
- Ensure code quality through testing, reviews, and observability
- Work within distributed systems that handle large-scale message streaming
- Implement secure authentication and authorization mechanisms
- Contribute to architectural decisions for cloud-native deployments
- Support CI/CD pipelines for automated testing and deployment
- Troubleshoot production issues across multiple layers of the stack
- Participate in agile planning and cross-functional coordination
- Refactor legacy components to support modern AI capabilities
- Enhance developer tooling for faster iteration on AI features
- Monitor system health and respond to incidents promptly
- Improve documentation for internal and external stakeholders
- Evaluate new technologies for fit within the AI and infrastructure stack
- Ensure compliance with data privacy and security standards
- Scale services to meet growing user and data demands
- Mentor junior engineers in best practices for fullstack and AI development
Nice to Have
- Experience with large language models or generative AI systems
- Contributions to open-source AI or infrastructure projects
- Familiarity with edge computing or IoT data flows
- Background in MQTT or similar messaging protocols
- Knowledge of stream processing technologies like Kafka or Flink
- Experience with AI model monitoring and lifecycle management
- Understanding of prompt engineering and AI interaction design
- Exposure to MLOps practices and tooling
- Prior work in developer-first product environments
- Familiarity with WebAssembly or low-level performance optimization
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid or remote options available
Team
Collaborative engineering team focused on scalable, real-time systems
Technology Stack
- Frontend: React, TypeScript, GraphQL
- Backend: Java, Spring Boot, Python
- AI: TensorFlow, PyTorch, Hugging Face, LangChain
- Infrastructure: Kubernetes, Docker, Helm, Terraform
- Cloud: AWS and GCP, with multi-region deployments
- Data: Kafka, MQTT, TimescaleDB, Prometheus
What We Value
- Ownership of features from concept to production
- Curiosity and continuous learning in fast-evolving domains
- Clear communication across technical and non-technical roles
- Focus on user impact and product usability
- Collaborative problem-solving and knowledge sharing
Visa sponsorship available for qualified candidates
