Lead AI Engineer

You will design scalable AI workflows, integrate autonomous agents into real-world applications, and help translate cutting-edge AI capabilities into reliable business solutions. 

•   6-8 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.
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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.

•    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.

Budgeted Salary Currency: INR