Full Stack AI Lead Developer

Skills this role screens for

About the role

Jabil is hiring for the role of Full Stack AI Lead Developer!

The work

Responsibilities of the Candidate

• End-to-End AI Application Development: Design, build, and deploy full-stack artificial intelligence applications from the ground up, seamlessly connecting robust backend AI services with responsive, user-friendly frontends.
• AI Model Integration & Orchestration: Integrate Large Language Models (LLMs), local model pipelines, vector databases, and multi-agent orchestration frameworks (such as RAG architectures) into production-ready software systems.
• Database Architecture & Performance Optimization: Architect, query, and optimize complex relational databases (PostgreSQL preferred), writing advanced SQL queries, multi-table joins, cursors, and stored procedures to guarantee high-performance data retrieval and storage.
• Backend Engineering & APIs: Develop high-performance, asynchronous backend services, RESTful APIs, and data ingestion pipelines primarily using Python to handle real-time data streaming and complex business logic.
• UI/UX & Dashboard Development: Build intuitive, responsive user interfaces and real-time operational dashboards using modern web frameworks to enable seamless human-AI interaction and telemetry visualization.
• Containerization & DevOps: Package applications using Docker and manage deployment, scaling, and cluster coordination using Kubernetes to ensure enterprise-grade reliability and fault tolerance.
• Cloud & Infrastructure Management: Provision, configure, and optimize cloud resources (primarily AWS) and high-performance computing environments (including GPU clusters) to support heavy AI workloads.
• Linux System Operations: Operate effectively within Linux environments, utilizing advanced shell utilities, system monitoring, and performance tuning for backend stability.
• Team Mentorship & Onboarding: Actively mentor, train, and guide junior developers and team members under your purview, rapidly bringing them up to speed on technical frameworks, coding standards, and best practices.
• Stakeholder Communication & Live Demos: Communicate effectively with diverse internal and external stakeholders, translating complex technical concepts into clear business value, and confidently conduct live, end-to-end software and AI application demonstrations.
• Quality & Continuous Improvement: Apply a quality-first mindset (incorporating principles like Lean Six Sigma where applicable) to debug issues, optimize system latency, automate testing, and ensure high reliability.
• Technology Exploration & Innovation: Stay on the cutting edge of AI advancements, rapidly evaluating, prototyping, and integrating emerging open-source tools, frameworks, and model updates into the enterprise stack.

Who they want

Requirements

• Core Technical Stack: Advanced Python development, AWS cloud infrastructure, and enterprise Linux administration.
• DevOps & Deployment: Expertise in containerization (Docker) and orchestration (Kubernetes) for large-scale enterprise deployments.
• AI & Innovation: Proven ability to build and deploy modern AI solutions (Multi-agent systems, RAG) and a passion for quickly adopting emerging technologies.
• Quality & Process: A background in Lean Six Sigma and other quality tools to ensure operational excellence and high-reliability software.