Lead AI Engineer

Bridge Global Careers & Events; India; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Bridge Global Careers & Events in India seeks an AI Engineer with 5+ years of experience to design, build, and deploy AI solutions using LLMs, Generative AI, RAG, and AI agents. You will integrate AI with enterprise systems and optimize model performance for scalable, production-ready applications.

You will collaborate with product teams, mentor peers, and drive best practices in AI safety, observability, and governance while evaluating tools and frameworks for adoption.

Qualifications

• Design, develop and deploy AI-powered applications using LLMs, Generative AI and ML.
• Build RAG systems, AI agents, chatbots, copilots and intelligent automation.
• Integrate AI with web apps, enterprise systems, databases and APIs.
• Evaluate, fine-tune and optimize AI models for accuracy and cost efficiency.
• Develop prompt engineering strategies and testing frameworks.

Responsibilities

• Design scalable AI architectures including vector databases and knowledge retrieval.
• Collaborate with product teams to translate requirements into AI solutions.
• Participate in code reviews, architecture discussions and technical decisions.
• Create documentation, architecture diagrams and implementation guides.
• Support deployment, troubleshooting and production optimization of AI apps.

Skills

Elasticsearch

AI Safety & Guardrails

MLOps

AI knowledge

Vector Databases

Agentic AI

LangGraph

Serverless Architectures

RAG

NLP

LangChain

Python

AI Agents & Multi-Agent Systems

Tools

LangChain

Python

Elasticsearch

Job description

Looking for an AI Engineer with 5 plus years of experience to build and deploy AI solutions using LLMs, Generative AI, RAG, AI agents, and Machine Learning. The role involves developing intelligent applications, integrating AI with enterprise systems, optimizing model performance, and implementing scalable, secure, production-ready AI solutions.

What we are looking for in you

• Design, develop, and deploy AI-powered applications and solutions using Large Language Models (LLMs), Generative AI, and Machine Learning technologies.
• Build and maintain Retrieval-Augmented Generation (RAG) systems, AI agents, chatbots, copilots, and intelligent automation solutions.
• Integrate AI models and services with web applications, enterprise systems, databases, APIs, and third-party platforms.
• Evaluate, fine-tune, and optimize AI models for accuracy, performance, reliability, and cost efficiency.
• Develop prompt engineering strategies and testing frameworks to improve AI response quality and user experience.
• Design and implement scalable AI architectures, including vector databases, knowledge retrieval systems, and agent workflows.
• Collaborate with product managers, designers, QA engineers, and business stakeholders to translate requirements into AI-driven solutions.
• Conduct research on emerging AI technologies, frameworks, models, and industry trends, and recommend adoption where appropriate.
• Establish monitoring, evaluation, and observability mechanisms for AI systems to ensure quality, compliance, and continuous improvement.
• Implement AI safety measures, guardrails, security controls, and responsible AI practices.
• Participate in code reviews, architecture discussions, and technical decision-making processes.
• Create technical documentation, architecture diagrams, implementation guides, and best practices.
• Support deployment, troubleshooting, and optimization of AI applications in production environments.
• Contribute to the organization’s AI strategy, innovation initiatives, and proof-of-concept development.
• Mentor team members and promote AI engineering best practices across projects.
  Research and experiment with new AI models, agentic frameworks, and emerging technologies.
• Build proof-of-concepts and validate new AI use cases before production implementation.
• Evaluate commercial and open-source AI tools, platforms, and frameworks.
• Define standards, governance practices, and reusable AI components for organization-wide adoption.

Key Skills

• Elasticsearch
• AI Safety & Guardrails
• MLOP
• AI knowledge
• Vector Databases
• Agentic AI
• LangGraph
• Serverless Architectures
• Retrieval-Augmented Generation (RAG)
• Natural Language Processing (NLP)
• langchain
• python
• AI Agents & Multi-Agent Systems

Office

India

Information Security & Data Protection

• Adhere to the organizations and clients applicable information security, confidentiality, privacy, and data protection requirements.
• Safeguard company and client information and use it responsibly, ensuring protection against unauthorized access, disclosure, alteration, loss, or misuse.