Staff Applied AI Engineer

What you’ll do

• Embed with internal teams across departments to deeply understand their workflows, gather requirements, identify high-impact AI use cases, and translate business needs into actionable technical solutions.
• Own and facilitate recurring AI office hours for drop-in support and guidance. Design and lead company-wide AI hackathons that inspire experimentation, knowledge sharing, and the discovery of innovative use cases.
• Evaluate, configure, and recommend the right AI tools and platforms for the organization. Stay on top of the rapidly evolving AI tooling landscape and make informed build-vs-buy recommendations.
• Design, develop, and deploy custom AI solutions tailored to specific team needs—leveraging LLMs, RAG architectures, agentic workflows, and automation frameworks to solve real business problems.
• Develop reusable playbooks, prompt libraries, workflow templates, how-to guides, and reference architectures that enable teams to self-serve on AI adoption.
• Architect and implement standardized, templatizable AI workflows that can be adapted and deployed across multiple teams and use cases, driving consistency and scale.
• Lead hands-on training sessions, workshops, and demos to teach teams how to effectively use AI tools and integrate them into their day-to-day work. Act as a force multiplier by building AI fluency organization-wide.
• Partner closely with Engineers, Business Systems, Security, Data Engineering, and other AI Solutions Engineers to integrate AI technologies into existing systems, ensuring security, compliance, and scalability.
• Contribute to the AI strategy and roadmap at the organizational level, aligning initiatives with business priorities and ensuring AI investments deliver maximum value.
• Present findings, demo solutions, share progress updates, and advocate for AI adoption with stakeholders ranging from individual contributors to executive leadership.

What you’ll bring

• Bachelor’s degree in Computer Science or equivalent experience. A graduate degree is a plus.
• 5+ years of experience in engineering, solutions engineering, or technical enablement roles, with a track record of deploying solutions that measurably enhance productivity.
• 3+ years of hands-on experience developing AI-centric products and solutions, including machine learning, generative AI, LLMs, RAG architectures, agentic frameworks, and prompt engineering.
• Deep proficiency in Python and experience with AI frameworks and integration of LLM models into applications; familiarity with cloud hosting platforms (AWS, GCP, Azure).
• Demonstrated ability to lead enablement programs—including running office hours, hackathons, training sessions, and creating scalable documentation and resources.
• Proven experience gathering requirements from non-technical stakeholders and translating them into well-scoped technical solutions.
• Exceptional ability to tackle open-ended, ambiguous problems in unstructured environments, synthesizing complex information into actionable plans and deliverables.
• Strong communication and presentation skills, with the ability to make complex AI concepts accessible to diverse audiences—from engineers to executives.
• A builder’s mindset: you are equally comfortable architecting a solution, writing production code, creating a training deck, and facilitating a workshop.
• A deep passion for AI and a genuine desire to help others harness its potential to transform how they work.