Lead Fullstack AI Development Engineer

We are seeking a highly talented and seasoned Lead Full-Stack Development Engineer with 8–12 years of
deep software engineering and machine learning production experience to drive the technical execution of our
AI product suites. Operating embedded directly within the AI Product & Engineering team, this pivotal role
serves as the primary engineering anchor responsible for designing, building, and deploying scalable,
high-performance AI applications, interactive user interfaces, and robust production systems.

You will lead the end-to-end development lifecycle, bridging the gap between foundational AI research models,
cloud data infrastructure, and user-facing software applications. Your core mission is to architect resilient
codebases, optimize inference pipelines, implement modern user interfaces, and establish automated DevOps
guardrails that seamlessly transform cognitive AI capabilities into enterprise-grade, scalable business solutions.

Required Qualifications

• Professional Experience: 8–12 years of proven success in full-stack software engineering roles, with at
least 3+ years actively leading technical teams and deploying commercial AI/ML-powered web products into
production environments.
• Front-End Engineering: Expert proficiency in React.js, Next.js, TypeScript, and modern state
management libraries (e.g., Redux, Zustand) alongside HTML5, CSS3, and Tailwind CSS.
• Core Backend Languages: Expert-level software development proficiency in Python, Java, or Go, paired
with deep experience in enterprise backend development environments and API design (RESTful,
GraphQL, WebSockets).
• AI & Machine Learning Frameworks: Advanced proficiency building with orchestration and deep learning
frameworks, specifically LangChain, LlamaIndex, PyTorch, TensorFlow, and agentic platforms (e.g.,
AutoGen, CrewAI).

• CI/CD & MLOps Infrastructure: Robust experience managing application containerization, cluster
orchestration, and automated pipelines utilizing Docker, Kubernetes, GitHub Actions, GitLab CI, or
Jenkins.
• AI & Database Ecosystems: Hands-on expertise with vector databases modern database stacks, and large-scale semantic search
infrastructures.
• Software Design Patterns: Superior understanding of distributed systems architecture, microservices,
asynchronous event-driven programming, and caching strategies.
• Agile Engineering Leadership: Documented success leading engineering sprints, mentoring mid-to-senior
frontend and backend developers, and serving as the ultimate system-level Subject Matter Expert (SME) to
achieve delivery goals

- Good business English skills (Written and spoken).