AI Engineer

Job highlights

• We are looking for a hands-on Applied AI Engineer with 3-8+ years of experience to build and maintain components of an enterprise-grade,multi-agent AI platform
• • Relevant certifications such as Microsoft Certified: Azure AI Engineer Associate

• Preferred / Good to Have . - Prior experience in legal,professional services,or document-heavy compliance-driven industries

• We are looking for a hands-on Applied AI Engineer with 3-8+ years of experience to build and maintain components of an enterprise-grade, multi-agent AI platform.
• Preferred Experience Profile
• • Ai Engineer
• • OverAll 3+ yrs with 2 years of practical AI/GenAI experience
• • Senior Ai Engineer
• • Over all 5 to 8 Yrs of Experience ( Java + Python ) with 3+ yrs of Strong Hands-on
• Ai/GenAI Experience
• • Lead Engineer -
• • 8+ Over all Experience ( Java + Python ) with 4+ yrs of Strong Hands-on Ai/ GenAI
• Experience
• Strong focus on implementation, delivery, and problem-solving in production environments
• Key Responsibilities
• Agent & AI Application Development
• • Build and maintain individual agents (e.g., Proofreader, Formatter, Document Converter,
• Paralegal, Reviewer/Approver, Document Router) per the architecture defined by the AI Architect.
• • Implement multi-agent orchestration logic, task decomposition, tool/function calling, and inter-
• agent communication using frameworks such as LangChain / LangGraph.
• • Build Retrieval-Augmented Generation (RAG) pipelines - document chunking, embeddings
• generation, and vector store integration - for grounding agent responses in SOPs, QC guidelines,
• and playbooks.
• • Implement agent-to-tool and agent-to-system integrations using standardized protocols such as
• Model Context Protocol (MCP).
• Required Skills & Experience
• • 3-5+ years of overall software engineering experience, including at least 2 years building AI/ML,
• GenAI, or LLM-powered applications.
• • Strong programming skills in Python Or Java with the ability to build and maintain enterprise-grade
• APIs, microservices, and integration layers.
• • Practical experience building or contributing to multi-agent / agentic AI systems, including agent
• orchestration and autonomous task execution.
• • Working knowledge of agent frameworks such as LangChain, LangGraph, or Semantic Kernel, and
• familiarity with the Model Context Protocol (MCP) for tool/data integration.
• • Experience implementing Retrieval-Augmented Generation (RAG) pipelines - embeddings,
• chunking strategies, and vector databases (e.g., Azure AI Search, Qdrant, Pinecone, or similar).
• • Familiarity with RBAC, SSO/authentication, audit logging, and secure coding practices for
• enterprise platforms.
• • Exposure to document intelligence / document processing systems (parsing, OCR,
• formatting/validation engines) is desirable.
• • Comfortable working with REST APIs, version control (Git), CI/CD pipelines, and Agile/Scrum
• delivery practices.
• • Strong problem-solving skills, attention to detail, and ability to work effectively within a distributed
• delivery team.
• • A2A/UI frameworks and conversational AI solutions
• Preferred / Good to Have
• • Prior experience in legal, professional services, or document-heavy compliance-driven industries.
• • Exposure to Databricks, LLM hosting/routing across multiple providers (OpenAI, Azure OpenAI,
• Anthropic, etc.), and LLM evaluation frameworks.
• • Relevant certifications such as Microsoft Certified: Azure AI Engineer Associate.
• Foundational Knowledge Expected
• Candidates should possess a working understanding of:
• • How Large Language Models (LLMs) work
• • LLM architecture and key concepts
• • Core Machine Learning concepts and terminology
• However, we are not evaluating candidates for deep research, model training, or scientist-level
• expertise.
• What We Are Looking For
• We need professionals who can quickly understand:
• • What we are building
• • The business problems we are solving
• • The platforms and applications we are developing and supporting
• • How to implement AI solutions in real-world enterprise environments
• The emphasis should be on practical application, engineering capabilities, solution design, and
• execution, rather than theoretical or academic depth.
• In summary: We are seeking a strong Applied AI Engineer profile with hands-on experience in modern
• GenAI and Agentic AI frameworks, capable of contributing immediately to development, delivery, and
• support of …