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About the role
As a Principal AI Engineer, you will play a pivotal role in defining the architecture and setting engineering standards for agentic AI systems and LLM applications. Your primary responsibility will be leading the development of critical components of the BGO AI Platform, including the agent runtime, integration and orchestration layer, HITL framework, and bespoke AI solutions for enterprise clients. Key Responsibilities: - Own the technical architecture of the BGO AI Platform core, including identity, memory, knowledge graph, agent orchestration, guardrails, and audit. Lead the development of critical subsystems. - Design and implement reliable, production-grade agentic workflows that involve long-running multi-step tasks with HITL checkpoints, escalation paths, and failure modes. - Define the integration of frontier models, private hosted models, and domain-specific small language models (SLMs) within the platform. Manage vendor risk effectively. - Establish engineering standards for evaluation, observability, safety, and cost efficiency to guide the team's development efforts. Your role will involve hands-on technical execution, including designing and shipping complex components, prototyping with frontier models, leading code and architecture reviews, and troubleshooting production issues. Additionally, you will be involved in AI-native product development, client-facing work, technical leadership, and mentorship activities. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field. - 10+ years of professional software engineering experience with at least 4 years focusing on AI/ML systems. - Demonstrated expertise as a technical lead on agentic AI systems, LLM-powered agents, and autonomous task execution. - Strong programming skills in Python and another language (TypeScript, Go, or Java), with experience in end-to-end system development. - Hands-on experience deploying AI systems on cloud platforms (AWS, GCP, Azure) with strong DevOps practices. - Track record of shipping complex AI systems end-to-end and experience in client-facing technical roles. In addition to technical qualifications, you should possess attributes such as technical depth, a bias for shipping, high agency, being a force multiplier, pragmatic judgment, excellent communication skills, and customer obsession. These qualities will be essential for success in this role. As a Principal AI Engineer, you will play a pivotal role in defining the architecture and setting engineering standards for agentic AI systems and LLM applications. Your primary responsibility will be leading the development of critical components of the BGO AI Platform, including the agent runtime, integration and orchestration layer, HITL framework, and bespoke AI solutions for enterprise clients. Key Responsibilities: - Own the technical architecture of the BGO AI Platform core, including identity, memory, knowledge graph, agent orchestration, guardrails, and audit. Lead the development of critical subsystems. - Design and implement reliable, production-grade agentic workflows that involve long-running multi-step tasks with HITL checkpoints, escalation paths, and failure modes. - Define the integration of frontier models, private hosted models, and domain-specific small language models (SLMs) within the platform. Manage vendor risk effectively. - Establish engineering standards for evaluation, observability, safety, and cost efficiency to guide the team's development efforts. Your role will involve hands-on technical execution, including designing and shipping complex components, prototyping with frontier models, leading code and architecture reviews, and troubleshooting production issues. Additionally, you will be involved in AI-native product development, client-facing work, technical leadership, and mentorship activities. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field. - 10+ years of professional software engineering experience with at least 4 years focusing on AI/ML systems. - Demonstrated expertise as a technical lead on agentic AI systems, LLM-powered agents, and autonomous task execution. - Strong programming skills in Python and another language (TypeScript, Go, or Java), with experience in end-to-end system development. - Hands-on experience deploying AI systems on cloud platforms (AWS, GCP, Azure) with strong DevOps practices. - Track record of shipping complex AI systems end-to-end and experience in client-facing technical roles. In addition to technical qualifications, you should possess attributes such as technical depth, a bias for shipping, high agency, being a force multiplier, pragmatic judgment, excellent communication skills, and customer obsession. These qualities will be essential for success in this role.