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Salary
≈ $24k – $64k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Staff · 8+ years exp

Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Oct 27, 2026. Verisk scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Verisk Analytics provides data analytics and risk models for the insurance industry. Its catastrophe models, claims data and rating services underpin much of property underwriting. The company also supplies fraud detection and climate risk analytics.

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.

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.

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.
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