Senior AI Engineer

Overview

Serve as a Senior AI Engineer in the AI Center of Excellence, leading the design, development, and deployment of enterprise AI and Generative AI solutions from concept through production. Work with Principal AI Engineers, enterprise architects, business stakeholders, product teams, and other technical teams to create scalable AI solutions and engineering standards.

What you'll do

• Lead the end-to-end delivery of AI and Generative AI solutions, from business discovery and solution design through deployment and operational support.
• Work directly with business stakeholders to identify opportunities, define requirements, prioritize use cases, and translate business challenges into practical AI solutions.
• Design scalable solution architectures leveraging LLMs, RAG, AI agents, enterprise knowledge sources, APIs, workflow automation, and cloud services.
• Develop and deploy production-grade AI applications, services, and copilots using Python, Azure AI, Azure OpenAI, Snowflake, and related enterprise technologies.
• Drive technical decisions across AI projects by evaluating architecture options, implementation approaches, trade-offs, risks, and long-term maintainability.
• Establish and implement testing, evaluation, and monitoring practices to ensure AI solutions are accurate, reliable, secure, and production ready.
• Collaborate with architects, data engineers, platform teams, security teams, and business partners to integrate AI capabilities into enterprise systems and processes.
• Build reusable frameworks, accelerators, templates, and engineering standards that improve delivery speed and enable scalable AI adoption.
• Provide technical leadership through architecture reviews, design guidance, code reviews, technical coaching, and sharing best practices across the AI CoE.
• Continuously evaluate emerging AI technologies and recommend innovative solutions that deliver measurable business value and strategic advantage.

What you'll need

• Master’s or Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 4-6 years of relevant professional experience in AI, machine learning, data, or software engineering.
• Minimum 1 year of hands-on experience designing, developing, and deploying AI, Machine Learning, or Generative AI solutions end-to-end.
• Strong Python development skills.
• Experience with software engineering principles including modular design, API development, testing, version control, secure coding practices, system integration, and maintainable application architecture.
• Strong understanding of modern Gen AI architectures including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, evaluation frameworks, deterministic orchestration, and AI solution architectures.
• Hands-on experience with AI application and orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, or equivalent technologies.
• Ability to operate in ambiguous environments, independently drive technical solutions, and lead initiatives from concept through production deployment.
• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Capacity to thrive in agile, fast-paced environments.
• Collaborative approach and leadership potential.
• Commitment to continuous learning and skill development.
• Effective task prioritization and project management across multiple initiatives.

Nice to have

• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, Microsoft Copilot Studio, Snowflake Cortex AI, or other enterprise AI platforms.
• Experience designing and developing enterprise AI applications, copilots, intelligent assistants, automation solutions, or agent-based systems deployed to business users.
• Experience with CI/CD, DevOps, MLOps, and LLMOps practices for enterprise AI solution deployment and support.
• Experience with containerization and cloud-native development technologies such as Docker, Kubernetes, Azure Container Apps, or Azure Kubernetes Service (AKS).
• Experience building AI-enabled applications and services using frameworks such as FastAPI, Flask, Streamlit, React, Next.js, .NET, or equivalent application development frameworks.
• Demonstrated experience leading the technical delivery of complex software, AI, or automation projects involving multiple stakeholders, systems, and business functions.
• Familiarity with enterprise governance controls for GenAI, including privacy, safety, and auditability.
• Experience optimizing inference costs/latency and implementing observability for AI features.

Details

• Location: Gurgaon.
• Applicants for employment opportunities in other countries must be able to meet the comparable export control requirements of that country and of the United States.