Principal AI ML Engineer

Job description

**About the Role** We are looking for a Principal AI/ML Engineer to lead the design, development, and scaling of Generative AI and Agentic AI systems on Google Cloud Platform (GCP). This is a leadership role where you will define architecture, set engineering standards, and drive enterprise-scale AI solutions using LLMs, RAG, and multi-agent systems. You will work closely with cross-functional teams to build scalable, secure, and high-performing AI platforms. **Key Responsibilities** **Architecture & Strategy** - Define architecture for GenAI, RAG, and agent-based systems - Drive technical decisions on tools, platforms, and design patterns - Establish standards for AI systems including scalability, safety, and cost **Solution Design & Delivery** - Lead development of production-grade GenAI solutions using Vertex AI - Build and scale agent-based systems with planning, tools, and memory - Design secure and scalable cloud architectures on GCP **Platform & Engineering Excellence** - Build reusable frameworks, prompts, and AI components - Implement LLMOps practices (CI/CD, monitoring, cost optimization) - Enable teams through reusable tools and best practices **Security & Responsible AI** - Ensure data privacy, governance, and compliance - Implement guardrails, monitoring, and audit mechanisms **Leadership** - Mentor engineers and lead design reviews - Drive collaboration across Product, Security, and SRE teams **Must-Have Skills** - Strong experience in Generative AI, LLMs, and RAG architectures - Hands-on experience with Google Cloud Platform (Vertex AI, BigQuery, Cloud Run, Pub/Sub) - Expertise in Agentic AI frameworks and multi-agent systems - Strong programming skills in Python (preferred) - Experience with LLMOps / MLOps, CI/CD, and automation - Good knowledge of data engineering and distributed systems - Experience with cloud security, IAM, and API management **Good to Have** - Experience with Apigee, Okta, or API security frameworks - Exposure to Document AI, Dataplex, or vector databases - Knowledge of multi-tenant architectures and cost optimization **Qualifications** - Bachelors or masters degree in computer science or related field - 12+ years of experience in software, data, or ML engineering - Proven experience building enterprise-scale AI platforms **Why Join Us** - Lead cutting-edge AI and GenAI innovation - Work on high-impact, enterprise-scale platforms - Opportunity to define architecture and influence strategy - Collaborative and forward-thinking engineering environment