Lead AI Engineer 4C

Overview

Design, develop, and deliver enterprise-scale AI solutions using Generative AI, Agentic AI, Machine Learning, and Data Science. Build production-ready AI applications, architect scalable solutions, and lead end-to-end delivery while collaborating with technical and business stakeholders and mentoring teams.

What you'll do

• Design, develop, and deploy enterprise AI, Machine Learning, and Generative AI solutions for complex business use cases.
• Build AI-powered copilots, intelligent assistants, autonomous agents, and workflow automation solutions using modern Agentic AI frameworks.
• Architect and implement Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, semantic search, and enterprise knowledge repositories.
• Develop scalable AI services, APIs, and cloud-native applications using Python and modern software engineering practices.
• Collaborate with Data Scientists to operationalize Machine Learning models and advanced analytics solutions in production.
• Drive prompt engineering, model evaluation, fine-tuning, and optimization of LLM-based applications.
• Define AI solution architecture, integration patterns, scalability, security, and deployment strategies across enterprise platforms.
• Implement MLOps and LLMOps practices, including model lifecycle management, monitoring, observability, governance, and Responsible AI.
• Lead technical discussions, perform architecture and code reviews, mentor development teams, and promote engineering best practices.
• Partner with clients and business stakeholders to understand requirements, define AI roadmaps, and deliver high-impact AI solutions.
• Drive innovation through Proof of Concepts (PoCs), reusable AI accelerators, and adoption of emerging AI technologies.
• Own the technical delivery of AI and Generative AI initiatives from solution design through production deployment.
• Provide technical leadership and mentor AI Engineers, Data Scientists, and cross-functional development teams.
• Drive architecture decisions, engineering standards, code quality, and AI best practices across projects.
• Collaborate with business leaders, clients, and solution architects to identify AI opportunities and define scalable solution strategies.
• Support solutioning, estimations, technical proposals, and innovation initiatives for AI-led engagements.
• Build reusable AI frameworks, accelerators, and reference architectures to improve delivery efficiency and scalability.

What you'll need

• 6–10 years of experience in AI/ML, Data Science, or enterprise software development.
• Strong programming expertise in Python, SQL, and API development.
• Hands-on experience with Machine Learning, Deep Learning, NLP, statistical modeling, and predictive analytics.
• Experience designing and deploying production-grade Generative AI and LLM-powered applications.
• Strong understanding of Prompt Engineering, RAG, embeddings, vector databases, semantic search, and AI evaluation techniques.
• Experience with Agentic AI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
• Experience integrating OpenAI, Azure OpenAI, Gemini, Claude, AWS Bedrock, or equivalent foundation models into enterprise applications.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP), Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of MLOps, LLMOps, Responsible AI, AI governance, and model monitoring.
• Excellent analytical, communication, stakeholder management, and mentoring skills.
• English language proficiency is required at Proficient - C2 level.
• Bachelor's or Master's degree (preferred) in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related field.

Nice to have

• Experience with Model Context Protocol (MCP), GraphRAG, Knowledge Graphs, or multimodal AI.
• Experience with Databricks, Snowflake, Spark/PySpark, or enterprise data platforms.
• Exposure to AI observability, evaluation frameworks, and guardrails for enterprise AI applications.
• AI/ML or Cloud certifications (Microsoft, AWS, Google Cloud, Databricks) are an added advantage.

Details

• Location: Gurgaon, India.
• Work mode: Hybrid.
• Work shift: Any (India).
• Employment type: Regular.