Principal AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop the AI architecture and technical strategy, overseeing implementation throughout the entire lifecycle from design to production.

• Create scalable machine learning platforms, pipelines, and workflow orchestration that facilitate model development and support event-driven, asynchronous operations at scale.

• Design and construct systems powered by large language models (LLMs), including prompt engineering, function/tool calling, multi-agent orchestration, retrieval-augmented generation (RAG) patterns, vector databases, embeddings, and streaming responses.

• Design and implement APIs and backend services that integrate AI functionalities with enterprise systems and third-party platforms.

• Lead the development and optimization of models, ensuring that innovative approaches transition into dependable, production-ready systems.

• Guarantee the reliability, security, and scalability of AI systems once deployed, including logging, monitoring, and debugging within production environments.

• Adopt an AI-forward mindset in daily tasks, utilizing tools like Claude, Cursor, and other contemporary AI assistants to deliver high-quality work efficiently.

• Collaborate with leadership to co-define the AI roadmap, participating as a peer in strategic technical discussions.

• Clearly communicate complex technical concepts to both engineering and non-engineering stakeholders, translating intricacies into actionable decisions.

• Collaborate with product, engineering, and data teams to ensure AI initiatives align with overarching business priorities.

• Establish and advocate for AI engineering standards that influence how the organization builds and operates AI systems.

• Mentor individuals across the organization, fostering engineering culture and nurturing the next generation of technical leaders.

• Make critical architectural decisions that hold significant organizational and cross-engagement implications.

• Propel the technical vision — determining not only what is built but also how AI engineering progresses at R&P over time.

⛳️ Requirements

• Over 7 years of experience in AI/ML engineering.

• Strong proficiency in Python programming.

• Robust software engineering background, encompassing system design, API design, code quality, and effective unit testing practices.

• Experience in designing and working with distributed systems and event-driven architectures.

• Expertise in MLOps and AI infrastructure, including model versioning, monitoring, deployment automation, and ensuring reproducibility.

• Familiarity with Amazon Quick, ServiceNow integration, Jira integration, AWS Bedrock, Agentic AI/ML (prompt engineering, agent development), and natural language querying/analytics.

• Excellent stakeholder communication skills, with the ability to convey technical depth to diverse audiences.

• Extensive experience with AWS, particularly with the AWS GenAI offerings; working knowledge of other cloud platforms is a plus.

• Knowledge of both SQL and NoSQL databases, including scalable design patterns.

• Experience with workflow orchestration tools and asynchronous system operations.

• Practical experience with LLM systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses.

• Familiarity with containerization technologies (e.g., Docker) and cloud-native AI architectural patterns.

• Awareness of AI governance and compliance considerations in production environments.

🏝️ Benefits

• Health insurance.

• 401(k) matching.

• Flexible working hours.

• Paid time off.

• Remote work options.