Principal Engineer - Artificial Intelligence/Machine Learning

Role Overview: As a Principal Engineer-AI/ML, your primary responsibility will be to own the architecture and technical roadmap for enterprise-scale Gen-AI, agentic AI, and ML platforms. You will act as the principal technical authority for AI/ML systems and automation initiatives. Additionally, you will define and enforce engineering standards, best practices, and design principles. Your role will involve evaluating emerging AI research and technologies to guide strategic adoption, and collaborating with Product, Data, and Engineering leadership to align AI capabilities with business objectives. Key Responsibilities: - Architect and oversee goal-driven, multi-agent systems capable of autonomous reasoning and execution. - Design and govern MCP-based infrastructures for secure, context-rich agent interactions with tools, APIs, databases, and cloud services. - Lead the design of long-running, stateful agent workflows with resilience, coordination, and dynamic task management. - Provide technical leadership for generative AI, multimodal pipelines, RAG architectures, and embeddings-based systems. - Ensure scalable, reliable, and observable ML/LLM deployments across environments. - Architect and oversee RLHF pipelines, feedback loops, and reward modeling frameworks to ensure continuous system improvement through structured human feedback and real-world interactions. - Mentor and guide senior AI/ML engineers and technical leads. - Provide technical oversight across multiple initiatives and teams, lead architectural reviews, technical planning, and delivery governance. - Promote a culture of engineering excellence, innovation, and experimentation. Qualifications Required: - 6-8 years of experience in AI/ML engineering, with a strong exposure to production-grade systems. - Proven experience in technical leadership or principal-level ownership. - Deep expertise in Python and modern ML/DL frameworks. - Strong experience in building distributed, scalable AI/ML systems. - Advanced knowledge of generative models, multimodal data, embeddings, and vector databases. - Experience with cloud-native platforms (AWS/GCP), Kubernetes, Docker, CI/CD. - Strong understanding of MLOps/LLMOps, observability, governance, and reliability. - Proven experience in designing multi-agent architectures and goal-driven workflows. - Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks. - Experience with MCP or secure agent-tool communication protocols. - Demonstrated experience mentoring engineers and influencing technical direction. - Strong communication skills with both technical and non-technical stakeholders. - Ability to balance hands-on execution with strategic technical leadership. Role Overview: As a Principal Engineer-AI/ML, your primary responsibility will be to own the architecture and technical roadmap for enterprise-scale Gen-AI, agentic AI, and ML platforms. You will act as the principal technical authority for AI/ML systems and automation initiatives. Additionally, you will define and enforce engineering standards, best practices, and design principles. Your role will involve evaluating emerging AI research and technologies to guide strategic adoption, and collaborating with Product, Data, and Engineering leadership to align AI capabilities with business objectives. Key Responsibilities: - Architect and oversee goal-driven, multi-agent systems capable of autonomous reasoning and execution. - Design and govern MCP-based infrastructures for secure, context-rich agent interactions with tools, APIs, databases, and cloud services. - Lead the design of long-running, stateful agent workflows with resilience, coordination, and dynamic task management. - Provide technical leadership for generative AI, multimodal pipelines, RAG architectures, and embeddings-based systems. - Ensure scalable, reliable, and observable ML/LLM deployments across environments. - Architect and oversee RLHF pipelines, feedback loops, and reward modeling frameworks to ensure continuous system improvement through structured human feedback and real-world interactions. - Mentor and guide senior AI/ML engineers and technical leads. - Provide technical oversight across multiple initiatives and teams, lead architectural reviews, technical planning, and delivery governance. - Promote a culture of engineering excellence, innovation, and experimentation. Qualifications Required: - 6-8 years of experience in AI/ML engineering, with a strong exposure to production-grade systems. - Proven experience in technical leadership or principal-level ownership. - Deep expertise in Python and modern ML/DL frameworks. - Strong experience in building distributed, scalable AI/ML systems. - Advanced knowledge of generative models, multimodal data, embeddings, and vector databases. - Experience with cloud-native platforms (AWS/GCP), Kubernetes, Docker, CI/CD. - Strong understanding of MLOps/LLMOps, observability, governance, and reliability. - Proven ex