Senior R&D AI Software Engineer

We are seeking an experienced Software Development Engineer to design and build end-to-end full-stack applications, encompassing intuitive frontend user interfaces and scalable backend services. This role involves developing responsive, user-friendly UI components using modern frameworks such as React or Vue, alongside building robust backend APIs and services (REST/GraphQL) to support application logic and data processing.

You will integrate AI/ML capabilities, including large language model (LLM) APIs and other inference services, into production-ready systems, while architecting efficient data pipelines for ingestion, transformation, and storage to enable AI-driven features. The role requires optimizing performance, scalability, and reliability across the full stack, and working closely with R&D, product, and design teams to translate concepts into functional, user-facing solutions. You will operate in a fast-paced R&D environment, rapidly prototyping and iterating while maintaining high engineering standards, and contributing to architectural decisions and team mentorship.

Key Responsibilities

• Design and develop end-to-end full-stack applications, including frontend interfaces and backend services
• Build responsive, high-performance UIs using modern frameworks (e.g., React, Vue)
• Develop and maintain scalable backend systems and APIs (REST/GraphQL)
• Integrate and operationalize AI/ML capabilities (e.g., LLM APIs, inference services) into production systems
• Architect and implement data pipelines for AI-driven applications
• Ensure performance, scalability, and reliability across frontend and backend systems
• Collaborate with cross-functional teams to deliver user-facing features
• Rapidly prototype and iterate on new ideas in an R&D environment
• Implement state management, caching, and asynchronous workflows for real-time interactions
• Design and manage cloud-based infrastructure (AWS)
• Apply best practices in code quality, testing, CI/CD, and system monitoring
• Monitor, debug, and optimize production systems (logging, observability, performance tuning)
• Ensure security and data privacy in system design
• Mentor junior engineers and contribute to technical leadership

Job Qualifications

Must-Have Qualifications

• Master's degree in Computer Science, Software Engineering, or a related field, with 5+ years of experience in full-stack software development
• Strong frontend expertise (React, Vue, or similar) and solid backend development skills (Python, Node.js, Java, or equivalent)
• Proven experience designing and building scalable APIs and systems, with strong fundamentals in system architecture and software design
• Hands-on experience integrating AI/ML services (e.g., LLM or inference APIs) into production applications
• Experience with cloud platforms (AWS) and modern development practices (version control, testing, CI/CD)
• Demonstrated experience building scalable summarization/information extraction pipelines and production-grade anomaly detection or predictive models on numerical/time-series data
• Familiarity with Agile/Scrum methodologies and rigorous validation of ML/GenAI systems (evaluation metrics, bias/risk assessment)
• Strong problem-solving skills, ability to work independently, and effective cross-functional communication
• Fluency in English, including technical communication

Strongly Preferred

• Experience building AI-powered applications involving LLMs, generative AI, or real-time inference systems
• Familiarity with ML workflows, model evaluation, and performance optimization
• Experience developing data-rich, interactive UIs (dashboards, visualizations, graphics-heavy applications)
• Hands-on experience with cloud-native architectures and containerization (Docker, Kubernetes)
• Experience with asynchronous processing, streaming systems, or real-time data pipelines
• Background in R&D or fast-paced product environments with rapid prototyping cycles
• Exposure to MLOps practices, monitoring, and observability tools
• Experience mentoring engineers or contributing to technical leadership
• Experience with Model Context Protocol (MCP) for standardized, secure integration between LLM systems and external data sources, tools, or enterprise services.