This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves working with BILL’s AI Product and Platform team to build the intelligence backbone that powers every AI and agent-driven experience across our products. - Architect large-scale LLM infrastructure, evaluation, and data systems. - Partner closely with product and engineering teams to launch new agents. - Drive down latency and cost while setting technical standards for AI across the company. - Lead the architectural strategy and design for end-to-end ML systems. - Own the operational roadmap for production-level inference, fine-tuning, and LLM orchestration at a large scale. - Develop and standardize reusable ML modeling frameworks and high-performance data pipelines. - Lead applied research initiatives and design experiments to push the boundaries of BILL's AI capabilities. - Oversee the evolution of BILL's data infrastructure for maximum scalability and long-term maintainability. - Identify emerging AI opportunities and transform them into core business goals. - Define and enforce best practices for ML engineering and mentor junior engineers. Qualifications - Proven leadership in leading complex, high-impact AI projects from ideation to production. - Deep expertise in building backend systems that support AI-driven products. - Expert-level experience in building complex data pipelines (ETL, cleaning, structuring). - Ability to bridge the gap between theoretical ML research and production engineering. - Strong communication skills with a history of shaping team goals and defining engineering standards. - Experience managing risks and trade-offs of complex AI deployments. Requirements - This position is eligible for visa sponsorship. - The estimated salary range for this role in San Jose is $216,000 — $269,900 USD. Benefits - 100% paid employee health, dental, and vision plans (choose HMO, PPO, or HDHP). - HSA & FSA accounts. - Life Insurance, Long & Short-term disability coverage. - Employee Assistance Program (EAP). - 11+ Observed holidays and wellness days and flexible time off. - Employee Stock Purchase Program with employee discounts. - Wellness & Fitness initiatives. - Employee recognition and referral programs. - And much more.

• Design and implement scalable MLOps/LLMOps platforms supporting the full ML lifecycle: data versioning, model training, evaluation, deployment, and monitoring • Build and maintain CI/CD pipelines for ML models and LLM applications with automated testing, validation, and rollback capabilities • Develop infrastructure-as-code (IaC) for reproducible, version-controlled ML environments • Architect model serving infrastructure with auto-scaling, A/B testing, and canary deployment capabilities • Build platforms for LLM fine-tuning, prompt management, and experimentation at scale • Implement evaluation frameworks for LLM performance, quality, safety, and cost optimization • Design and deploy enterprise-grade AI agents and copilots with robust monitoring and guardrails • Establish LLM observability: token usage tracking, latency monitoring, prompt/response logging, and cost attribution • Own uptime, reliability, and performance of ML/LLM services (SLIs/SLOs) • Implement comprehensive monitoring, alerting, and incident response for ML systems • Participate in on-call rotations and drive post-incident reviews to improve system resilience • Build automation and tooling to reduce toil and accelerate ML development velocity • Partner with ML Engineers and Data Scientists to translate research into production-ready systems • Collaborate with platform and infrastructure teams on cloud architecture and resource optimization • Mentor team members on MLOps best practices, production ML patterns, and operational excellence • Drive technical decisions on tooling, frameworks, and architectural patterns

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts. • Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale. • Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability. • Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights. • Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes. • Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement. • Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Dam Engineer will have experience with Dams in a number of different areas of focus which can include Structural Engineering of Dams, the H&H design criteria for Dams or with the Geotechnical Engineering Standards for Dams. This role offers an exceptional career opportunity for a proven self-starter with a customer-focused approach, capable of leading medium to large-scale projects with a strong emphasis on delivering the highest quality results. - Designing and analyzing various types of dam embankments and flood control structures, focusing on seepage, slope stability, and dam safety issues. - Designing and analyzing reinforced concrete hydraulic structures, such as spillways, outlet works, and stilling basins for complex sites. - Independently applying advanced theories, concepts, and principles of engineering to address critical issues and unique conditions. - Participating in the development of project design concepts and criteria, including research on large or complex project elements. - Leading the interpretation, organization, execution, and coordination of large or complex engineering assignments. - Acting as a technical specialist in the preparation of proposals. - Managing project teams, including potential integration across multiple disciplines. - Serving as Project Manager, Client Manager, and/or Proposal Manager as needed. - Conducting QA/QC reviews to ensure high-quality deliverables. - Supervising a team of engineers and other technical specialists, as applicable. - Collaborating closely with clients to ensure satisfaction and contribute to business development initiatives. - Preparing engineering memorandums, reports, design drawings, and specifications. - Providing observation support and guidance to construction management staff during project construction phases. - Preparing engineering design cost proposals and assisting with marketing and business development efforts as required. Qualifications - Registered Professional Engineer (PE) in Colorado or ability to obtain. - Bachelor’s Degree in Civil, Structural or Geotechnical Engineering is required. - 5-10 plus years of experience in water resources, mining, or dam projects. - Experience with AutoCAD and Microsoft Office Suite. - Field experience with geotechnical related explorations and construction activities. - Strong analytical and report/proposal writing skills. - Strong written and verbal communication skills and ability to work independently and within a team environment. - Project Management experience (PMP) and/or advanced technical certification (BCEE) is preferred. Requirements - Master's Degree preferred. - Familiarity with GeoStudio. - MSHA certification. - Prior supervision of staff. - Project Management experience (PMP) and/or advanced technical certification (BCEE). Compensation - The salary range for this role is $95,000 - $135,000. Salary is dependent upon experience and geographic location. Benefits - Hybrid (in-person and remote) work environment. - Comprehensive benefits package including wellness programs, parental leave, and pet insurance, in addition to medical, dental, vision, disability, and life insurance. - Tax-deferred 401(k) savings plan. - Competitive paid-time-off (PTO) accrual. - Tuition reimbursement for continued education. - Commitment to professional development, access to internal and external training programs, and support of active participation in professional organizations. - Incentive compensation for eligible positions.