Full Stack AI Lead Developer

Jabil; New Delhi; On-site; INR 1,800,000 - 3,500,000; Full time

Job summary

Jabil in New Delhi, India, seeks an experienced Backend Engineer to lead AI-enabled application development, integrating LLMs, data pipelines, and real-time dashboards for enterprise needs. You will architect scalable backends, collaborate closely with frontend teams, and ensure robust API delivery.

You will mentor engineers, optimize performance, and manage Docker/Kubernetes deployments on AWS, while staying ahead of open-source tools and model updates to drive innovation and reliability across

Qualifications

• Advanced Python development
• AWS cloud infrastructure
• Enterprise Linux administration
• Docker & Kubernetes orchestration for large-scale deployments
• Multi-agent systems / RAG
• Lean Six Sigma and quality tools

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 into production-ready software systems.
• Database Architecture & Performance Optimization: Architect, query, and optimize complex relational databases (PostgreSQL preferred), writing advanced SQL queries and stored procedures for high-performance data retrieval.
• Backend Engineering & APIs: Develop high-performance, asynchronous backend services, RESTful APIs, and data ingestion pipelines using Python for real-time data streaming and complex business logic.
• UI/UX & Dashboard Development: Build intuitive, responsive user interfaces and real-time dashboards for human-AI interaction and telemetry visualization.
• Containerization & DevOps: Package applications using Docker and manage deployment, scaling, and cluster coordination using Kubernetes.
• Cloud & Infrastructure Management: Provision, configure, and optimize AWS resources and GPU clusters for heavy AI workloads.
• Linux System Operations: Work in Linux environments with advanced shell utilities and performance tuning.
• Team Mentorship & Onboarding: Mentor and train junior developers and team members on frameworks and coding standards.
• Stakeholder Communication & Live Demos: Communicate complex concepts to stakeholders and conduct live, end-to-end demonstrations.
• Quality & Continuous Improvement: Apply Lean Six Sigma principles to debug, reduce latency, automate testing, and improve reliability.
• Technology Exploration & Innovation: Evaluate and integrate emerging open-source tools and model updates into the stack

Skills

Python

AWS

Linux

Docker

Kubernetes

AI/ML

Lean Six Sigma

Tools

PostgreSQL

Job description

• 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.

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

We are looking for a candidate who combines deep technical expertise with a strong quality-first mindset. Specifically, the ideal candidate should have hands-on experience with:

• 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.