Full Stack AI Lead Developer

Jabil; New Delhi; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Jabil in India is seeking a seasoned AI/Backend Engineer to architect and deliver end-to-end AI applications, spanning data pipelines, model integration, and responsive dashboards. You will design scalable backend services in Python, deploy on AWS, manage Linux environments, and mentor junior developers while driving quality and innovation across the tech stack.

Responsibilities include containerization with Docker, orchestration via Kubernetes, and building real-time dashboards for operational

Qualifications

• Strong Python development experience with backend systems.
• Experience with AWS cloud infrastructure.
• Proficiency in Linux system administration.
• Hands-on containerization with Docker and Kubernetes.
• Knowledge of LLMs, RAG, and AI model deployment.
• Lean Six Sigma or quality tooling experience.

Responsibilities

• End-to-End AI application development: design, build, and deploy full-stack AI applications with backend services and frontends.
• AI model integration & orchestration: integrate LLMs, local model pipelines, vector databases, and multi-agent frameworks (RAG).
• Database architecture & optimization: design and optimize PostgreSQL databases with advanced SQL and stored procedures.
• Backend engineering & APIs: develop asynchronous Python services, RESTful APIs, and data ingestion pipelines for real-time data streaming and business logic.
• UI/UX & dashboard development: build intuitive UIs and real-time dashboards for human-AI interaction and telemetry visualization.
• Containerization & DevOps: Docker and Kubernetes for deployment, scaling, and cluster coordination.
• Cloud & infrastructure management: AWS and GPU-enabled HPC environments for heavy AI workloads.
• Linux system operations: operate in Linux with advanced shell utilities, monitoring, and performance tuning.
• Team mentorship & onboarding: mentor and onboard junior developers and engineers.
• Stakeholder communication & live demos: present complex concepts to stakeholders and conduct live demonstrations.
• Quality & continuous improvement: lean practices to reduce latency, automate testing, and ensure reliability.
• Technology exploration & innovation: evaluate and prototype emerging AI tools and models.

Skills

Advanced Python

AWS cloud

Linux administration

Containerization

Kubernetes

AI & RAG

Lean Six Sigma

Tools

Docker

Kubernetes

PostgreSQL

REST APIs

Git

Job description

Job Responsibilities

• 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.

Desired Criteria

• 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.