Lead AI Engineer

Verisk; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Verisk in Hyderabad, India seeks a Lead AI Engineer to architect and build production-grade AI systems powered by large language models and autonomous agents. You will design scalable AI workflows and integrate agents into real-world applications to deliver reliable business solutions.

The role requires 8+ years in software development (Dotnet/React/full-stack), hands-on Generative/Agentic AI, strong Python, REST APIs, and experience with LLMs, embeddings and RAG.

Qualifications

• 8+ years of professional software development with leadership experience.
• Minimum 2 years hands-on Generative AI or agentic AI work.
• Strong Python and backend engineering fundamentals.
• Experience designing RESTful APIs and scalable architectures.
• Familiarity with LLMs, embeddings, RAG workflows, and governance.

Responsibilities

• Architect and design production-ready AI systems using Generative and agentic frameworks.
• Build, deploy and monitor AI workflows with LLMs and multi-agent coordination.
• Integrate AI applications with existing software landscapes.
• Apply prompt engineering, MCP patterns and context management.
• Mentor developers and drive engineering best practices.

Skills

Generative AI

Agentic AI

Python

REST APIs

LLM

Distributed systems

Mentorship

Tools

Docker

Kubernetes

Git

CI/CD

Vector databases

Job description

Job Description

We are seeking a

Job Description

We are seeking a Lead AI Engineer with strong software engineering foundations and hands‑on experience in Generative and Agentic AI. In this role, you will architect, design and build production-grade AI systems powered by large language models and intelligent agents. You will design scalable AI workflows, integrate autonomous agents into real‑world applications, and help translate cutting‑edge AI capabilities into reliable business solutions.

Responsibilities

• Architect and Design production-ready applications leveraging Generative AI and agentic AI frameworks.
• Build, Deploy and Monitor intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines.
• Integrate new AI applications with traditional pre-existing applications.
• Implement prompt engineering strategies, retrieval‑augmented generation (RAG), and contextual memory systems.
• Implement various AI coding techniques (context‑driven, spec‑driven development etc.).
• Architect and implement AI agents capable of reasoning, planning, and multi‑step task execution.
• Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems.
• Provide mentoring and technical guidance to developers and other AI Engineers.
• Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems.
• Optimize latency, cost efficiency, and scalability of AI‑powered workflows.
• Collaborate with product managers, data teams, and software engineers to deliver AI features.
• Ensure reliability through testing, logging, monitoring, and observability of AI behavior.
• Own architectural decisions, coding standards, and best practices.
• Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI‑driven engineering approaches.
• Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows.
• Support implementation of governance controls related to data handling, model behavior monitoring, and risk mitigation.
• Research emerging AI tools and frameworks to continuously improve system capabilities.
• Document AI workflows and maintain reproducible engineering processes.

Qualifications

• 8+ years of professional software development experience (Dotnet/React/Full-stack) with mentorship/team leadership experience.
• Minimum 2 years of hands‑on experience building applications using Generative AI or agentic AI systems.
• Strong proficiency in Python and backend engineering principles.
• Experience designing RESTful APIs and scalable service architectures.
• Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines.
• Working knowledge of AI governance principles, responsible AI practices, or compliance considerations.
• Familiarity with agent frameworks and autonomous decision workflows.
• Understanding of data structures, system design, and performance optimization.
• Strong analytical thinking and problem‑solving skills.

Preferred Qualifications

• Experience deploying AI applications in cloud environments (preferably AWS).
• Familiarity with vector databases and knowledge retrieval architectures.
• Experience working with Git, CI/CD pipelines, and production deployments.
• Exposure to containerization and orchestration tools (Docker, Kubernetes).
• Experience implementing evaluation or monitoring pipelines for AI agents.
• Knowledge of AI safety, guardrails, and responsible AI practices.
• Knowledge of distributed systems or event‑driven architecture.

About Us

Our People, Our Culture

For more than 50 years, Verisk has helped property and casualty insurers make smarter decisions about risk through AI‑powered risk modeling, advanced analytics, and technology solutions spanning the entire policy lifecycle. We are a leading strategic data, analytics, and technology partner to the global insurance industry, guided by core values of learning, caring, and results while maintaining the highest ethical standards as stewards of the industry's most comprehensive datasets. Learn more about Verisk and what we are doing within the insurance industry.

For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work® for outstanding workplace culture in the US, the fourth consecutive year in the UK, Spain, and India, and the second consecutive year in Poland. In addition, we’ve been recognized by The Wall Street Journal as one of the Best‑Managed Companies and by Forbes as a World’s Best Employer, testaments to the value we place on workplace culture.

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