Job Description: Senior Lead AI Engineer – Gen AI Platform

Location-Remote

Job Summary

The Senior Lead AI Engineer – Gen AI Platform is responsible for designing, developing, and scaling enterprise-grade Generative AI platforms and solutions. This role provides technical leadership in building AI-powered applications, developing reusable AI services, integrating Large Language Models (LLMs), and implementing MLOps and LLMOps best practices. The position collaborates with product, engineering, data science, and business teams to deliver secure, scalable, and high-performing AI solutions.

Key Responsibilities

• Lead the architecture, design, and development of enterprise Generative AI platforms and applications.
• Design and implement AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering techniques.
• Build reusable AI services, APIs, SDKs, and platform capabilities for enterprise adoption.
• Develop and optimize AI pipelines using Python and modern AI frameworks.
• Integrate foundation models from providers such as OpenAI, Anthropic, Google, Meta, or open-source models.
• Implement vector databases, embeddings, semantic search, and knowledge retrieval solutions.
• Establish MLOps/LLMOps practices including model deployment, monitoring, evaluation, governance, and lifecycle management.
• Ensure AI solutions meet enterprise security, compliance, privacy, and responsible AI standards.
• Collaborate with cross-functional teams to define AI strategy, architecture, and technical roadmaps.
• Mentor engineers and provide technical leadership across AI initiatives.
• Evaluate emerging AI technologies and recommend platform improvements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Strong programming skills in Python and experience with REST APIs and microservices.
• Experience building applications using Large Language Models (LLMs) and Generative AI frameworks.
• Hands-on experience with LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks.
• Experience implementing Retrieval-Augmented Generation (RAG), embeddings, and vector databases.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Docker, Kubernetes, CI/CD, and DevOps practices.
• Strong understanding of software architecture, distributed systems, and scalable platform design.
• Excellent leadership, communication, and stakeholder management skills.

Preferred Qualifications

• Experience with Azure OpenAI, Amazon Bedrock, Google Vertex AI, or similar AI platforms.
• Experience with MLflow, Kubernetes, Airflow, or other MLOps/LLMOps tools.
• Familiarity with AI governance, model evaluation, prompt optimization, and responsible AI practices.
• Knowledge of enterprise integrations, APIs, event-driven architectures, and data engineering.
• Experience leading AI platform teams or enterprise AI transformation initiatives.