Ai Forward Deployed Engineer - Java & Genai

About the Role

The AI Forward Deployed Engineer partners with business stakeholders to identify AI use cases, build prototypes, and deliver production-grade GenAI solutions. The role focuses on hands-on development and integration of LLMs, RAG, agents, cloud deployments, and enterprise APIs to create scalable, secure, and observable systems.

Fast prototyping with LLMs, RAG, and agent workflows; building production AI copilots and integrations.

Location: Noida, Pune, Mumbai (All Areas)

Type: Full Time, Permanent

Posted: Yesterday

Category: AI/ML & Data

Vibe Markers: 💻 Open Source, 🔥 Hot

Experience Level: Senior

Job Description

Role

The AI Forward Deployed Engineer partners with business stakeholders to identify AI use cases, design and build prototypes, and deliver production-grade AI solutions integrating LLMs, RAG, agents, and enterprise systems. The role covers end-to-end development including solution architecture, system design, deployment, monitoring, and optimization in cloud environments.

Key Responsibilities

• Identify and define AI use cases with business stakeholders
• Design and develop AI/ML and GenAI-based solutions (LLMs, RAG, agents)
• Build and deploy production-ready applications, copilots, and automation tools
• Integrate solutions with enterprise systems, APIs, microservices, and databases
• Collaborate with cross-functional teams to ensure scalability, security, and reliability
• Rapidly iterate prototypes based on feedback and performance metrics
• Monitor and optimize solutions for accuracy, latency, and cost
• Create technical documentation and deployment guides
• Advise stakeholders on AI capabilities, risks, and best practices

Requirements

• Strong programming skills in Python, JavaScript/TypeScript, and Java
• Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agentic workflows
• Experience with cloud platforms (Azure, AWS, GCP) and API-based development
• Familiarity with vector databases (Pinecone, FAISS), embeddings, and retrieval systems
• Experience with MLOps practices and CI-CD pipelines
• Solid system design and solution architecture skills
• Experience with security, compliance, monitoring, and observability in AI systems
• Ability to work closely with business stakeholders in customer-facing, fast-paced environments
• Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent (preferred)

Tech Stack

Python, JavaScript, TypeScript, Java, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, Agentic Workflows, APIs, Microservices, Azure, AWS, GCP, Pinecone, FAISS, React, Angular, Vector Databases, Embeddings, MLOps, CI-CD pipelines, Monitoring & Observability tools

Skills

System Design, Solution Architecture, Communication, Problem Solving, Stakeholder Management, Rapid Prototyping, Collaboration, Monitoring & Observability, Security & Compliance, MLOps, CI/CD, Debugging, Customer-facing