Full Stack Engineer

Project description

We are seeking a highly skilled Full Stack AI Engineer to design, develop, and maintain AI-enabled applications and intelligent agents that drive business automation and enhance user experiences. The role involves building scalable Java-based backend services, modern frontend applications, AI/GenAI capabilities using Python, and robust CI/CD pipelines. The candidate will work within a pod-based agile delivery model and take ownership of end-to-end solution delivery, quality, and operational readiness.

Responsibilities

Design, develop, and maintain AI-enabled applications, intelligent agents, and enterprise solutions.

Develop scalable Java-based backend services, APIs, and microservices.

Build responsive and intuitive frontend applications and user experiences.

Implement AI, Machine Learning, and Generative AI capabilities using Python and related frameworks.

Integrate Large Language Models (LLMs), AI agents, and conversational AI solutions into business applications.

Develop and execute automated testing strategies and promote shift-left quality practices.

Build, manage, and optimize CI/CD pipelines to support automated deployments.

Produce technical documentation, architecture artifacts, and knowledge-sharing materials.

Support production deployments, operational readiness, and post-deployment activities.

Collaborate within a pod-based delivery model, taking accountability for delivery outcomes and business value.

Troubleshoot application issues and drive continuous improvement initiatives.

Skills

Must have

• 7+ years of experience in Full Stack Application Development.
• Strong experience in Java, Spring Boot, REST APIs, and Microservices architecture.
• Proven expertise in Python development for AI/ML and Generative AI solutions.
• Experience building AI-enabled applications, chatbots, AI agents, or LLM-based solutions.
• Strong frontend development experience using React, Angular, JavaScript, or TypeScript.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, Azure DevOps, or similar platforms.
• Strong understanding of automated testing frameworks and quality engineering practices.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Excellent problem-solving, collaboration, and communication skills.
• Experience working in Agile/Scrum or pod-based delivery environments.
• Generative AI & LLMs:
• OpenAI / Azure OpenAI APIs
• Prompt Engineering
• RAG (Retrieval Augmented Generation)
• LangChain / LangGraph
• AI Agents
• Vector Databases (FAISS, ChromaDB, Pinecone anyone they can learn and come)
• FastAPI-based AI services
• LLM Evaluation and Testing