Associate Principal, Artificial Intelligence Engineering
About The Position
The Associate Principal, Artificial Intelligence Engineering will lead the design, deployment, and optimization of generative AI data solutions across OCC, establishing architectural standards and best practices. The role develops Python software and advanced machine learning solutions, integrates enterprise data sources with AI platforms such as Claude Enterprise, and builds enterprise RAG systems and complex LLM agent workflows. It provides technical leadership and mentoring, advises product development teams on AI implementation, and partners with product managers, designers, domain experts, and executive stakeholders to prototype and deploy AI-enabled data products and set a long-term technical vision and roadmap. The position leads backend infrastructure design for robust, scalable, and secure AI data services; administers AWS Bedrock to provision and manage large language models; and develops evaluation frameworks using MMLU and TruthfulQA. It establishes standards for prompt engineering and model versioning, applies observability, evaluation, benchmarking, and continuous improvement practices, and defines KPIs to track AI data utilization, effectiveness, and integration. Enterprise RAG systems with embedded vector databases are deployed and configured using Amazon Q Business. Up to 40% telecommuting is permitted.
Requirements
- Master's degree in computer science, software engineering, analytics, or a related field.
- Two years of experience as a data analyst, data analytics engineering associate, or in a related role.
- Work experience developing Python software, including command-line tools, data processing and extraction scripts, reusable tooling, and platform integration utilities, for enterprise data systems and AI platforms including Claude Enterprise.
- Work experience designing and implementing integrations between cross-platform enterprise data sources and downstream data and AI platforms, including Claude Enterprise, using Python, Model Context Protocol (MCP) servers, and enterprise platform connectors.
- Work experience deploying and configuring enterprise RAG systems with embedded vector databases using Amazon Q Business.
- Work experience administering AWS Bedrock to provision and manage large language models and building model evaluation frameworks using MMLU and TruthfulQA.
Responsibilities
- Collaborate with cross-functional teams to integrate AI data solutions into products.
- Develop and deploy data machine learning models and integrate AI capabilities across platforms.
- Develop Python software, including command-line tools, data processing and extraction scripts, reusable tooling, and platform integration utilities for enterprise data systems and AI platforms such as Claude Enterprise.
- Advise product development teams on AI implementation best practices.
- Lead the design, deployment, and optimization of Gen AI data solutions across OCC, establishing architectural standards and best practices.
- Lead the development of RAG systems and complex LLM agent workflows, and provide technical leadership and mentoring.
- Collaborate with product managers, designers, and domain experts to prototype and deploy AI-enabled data products.
- Deploy and configure enterprise RAG systems with embedded vector databases using Amazon Q Business.
- Apply observability, evaluation, benchmarking, and continuous improvement practices to deployed AI data systems.
- Establish enterprise-wide standards for prompt engineering and model versioning.
- Design and implement integrations connecting enterprise data sources to downstream data and AI platforms using Python, MCP servers, and enterprise platform connectors.
- Lead technical design and implementation of robust, scalable, and secure backend infrastructure for AI data services.
- Develop the technical vision and long-term roadmap for AI data systems at OCC with executive stakeholders.
- Develop KPIs to monitor AI data utilization, effectiveness, and integration.
- Administer AWS Bedrock to provision and manage large language models and build model evaluation frameworks using MMLU and TruthfulQA.
Benefits
- Standard benefits package
- Collaborative and supportive environment that encourages work-life balance and employee wellness
- Hybrid work environment with up to two days per week of remote work
- Tuition reimbursement
- Student loan repayment assistance
- Technology stipend for connecting to the network while working remotely
- Generous paid time off
- Parental leave
- 401(k) employer match
- Medical, dental, and vision benefits
- Employees may be eligible for a discretionary bonus; bonuses are not guaranteed
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What This Job Offers
Job Type
Full-time
Career Level
Principal
