Lead AI Engineer

Verisk

Lead AI Engineer for Verisk, architecting and building AI systems using Generative AI and large language models in Hyderabad. Focused on scalable workflows and real-world applications.

Posted 5/26/2026full-timeHyderabad • 🇮🇳 IndiaSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerKubernetes.NETPythonReact

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Generative AIagentic AIPythonRESTful APIsLLM APIsembeddingsvector searchRAG pipelinesdata structuresperformance optimization

Soft Skills

mentorshipteam leadershipanalytical thinkingproblem-solvingcollaborationtechnical guidancecommunicationbest practices promotionresponsible AI practicesresearch