- Design and implement AI-driven workflows that generate actionable, human-directed insights. - Build and optimize LLM-powered systems for summarization, recommendation, classification, and orchestration. - Implement agentic AI patterns that operate under explicit human guardrails and approval flows. - Translate unstructured data into structured Action Points™ aligned with user goals. - Develop and maintain prompt architectures and evaluation frameworks for consistent AI output quality. - Architect and develop semi-autonomous AI agents with mandatory human-in-the-loop control points, safety guardrails, and review checkpoints. Voice to Text - Design and implement AI-driven voice workflows that generate actionable, human-directed insights. - Architect real-time speech-to-text pipelines for AI control, command execution, and Action Point generation. - Implement low-latency voice ingestion using Azure Speech SDK for real-time transcription, intent detection, and multilingual support. - Ensure voice inputs are securely processed, auditable, and aligned with human authorization and approval flows. - Translate spoken input into structured, human-directed Action Point that govern downstream AI agents. Integration & Deployment - Deploy AI services using FastAPI and integrate them securely with backend systems. - Collaborate with frontend and backend engineers to expose AI capabilities via secure APIs. - Ensure AI systems scale reliably in cloud environments (Azure-based). Performance, Ethics & Governance - Optimize inference latency, throughput, and cost efficiency. - Implement observability, logging, and monitoring for AI workflows. - Apply responsible AI principles: transparency, auditability, and human override by design.

• Build a monthly roadmap of AI workflows to design and ship, prioritized by productivity or cost impact, for every department (except Product and Engineering) • Identify manual, repetitive work across departments and design AI-driven workflows to replace or accelerate it • Ship the workflows you scope: configure tools, build automations, and get them into daily use, not just document recommendations • Iterate and fine-tune workflows post-launch based on usage and feedback • Support system implementations for AI and adjacent tools, partnering with the CTO and Engineering on technical requirements and data access • Connect AI tools into core business systems (CRM, HRIS, finance tools, Slack, etc.), so workflows run inside the systems teams already use • Evaluate and pilot new AI tools for specific departments and use cases, and recommend what to adopt, pause, or retire • Train department teams on the workflows and tools you build, and follow up to make sure they're actually being used • Troubleshoot adoption issues directly with end users rather than escalating them • Track usage and cost of AI tools by team and use case, and run monthly ROI reporting • Report progress monthly to the CTO on workflow delivery, adoption, and productivity/cost impact • Level up teams to build and own their own AI workflows over time, so departments grow more self-sufficient rather than depending on you for every change

• Build, scale, and run biosecurity evaluations on frontier AI systems • Perform pre-release and post-release assessments of frontier and open-source AI models • Build adapters for models, identify and troubleshoot unexpected agent behaviors • Ensure evaluations are methodologically rigorous • Improve evaluations to use state-of-the-art agent frameworks, jailbreaking methods, and elicitation strategies • Develop and improve internal tools for capability assessments at scale • Contribute to and maintain cloud infrastructure

Role Description We're looking for an AI Enablement Engineer to drive AI adoption across every team at Applause. You'll build and maintain a monthly roadmap of AI-powered workflows for departments like Sales, Customer Success, Marketing, Finance, and HR/TA, then actually implement them: - Standing up tools - Wiring integrations into our core systems - Training the team on how to use them - Tracking whether they're moving the needle This is a builder role, and you'll work closely with our CTO and Chief Architect, who own the broader AI vision and governance, while you own execution. Qualifications - Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (or equivalent hands-on experience) - 2–4 years of experience in AI/LLM implementation, workflow automation, technical business operations, or a related hands-on technical role - Able to write and modify code for simple, internal business applications (even if AI writes most of it)—production-grade or engineering-quality code is not required - Demonstrated experience building integrations or automations (e.g., Zapier, Make, APIs, low-code/no-code platforms) - Working knowledge of modern AI tools (Claude, Copilot, and similar) and how to apply them to business workflows - Comfortable working cross-functionally with non-technical teams (Sales, CS, Marketing, Finance, HR) to scope and deliver workflows - Strong communicator who can train and troubleshoot with non-technical users - Detail-oriented with strong ownership over initiatives, start to finish - Very effective in a remote work environment Requirements - Build a monthly roadmap of AI workflows to design and ship, prioritized by productivity or cost impact, for every department (except Product and Engineering) - Identify manual, repetitive work across departments and design AI-driven workflows to replace or accelerate it - Ship the workflows you scope: configure tools, build automations, and get them into daily use, not just document recommendations - Iterate and fine-tune workflows post-launch based on usage and feedback - Support system implementations for AI and adjacent tools, partnering with the CTO and Engineering on technical requirements and data access - Connect AI tools into core business systems (CRM, HRIS, finance tools, Slack, etc.), so workflows run inside the systems teams already use - Evaluate and pilot new AI tools for specific departments and use cases, and recommend what to adopt, pause, or retire - Train department teams on the workflows and tools you build, and follow up to make sure they're actually being used - Troubleshoot adoption issues directly with end users rather than escalating them - Track usage and cost of AI tools by team and use case, and run monthly ROI reporting - Report progress monthly to the CTO on workflow delivery, adoption, and productivity/cost impact - Level up teams to build and own their own AI workflows over time, so departments grow more self-sufficient rather than depending on you for every change Benefits - 100% remote w/ no office mandate - Unlimited PTO - 22 official company holidays - Health care - Life insurance - Stock options - Amazing colleagues - Energetic culture that is positive and celebrates together - Inspiring mission & software product - Ability to grow your career by being early in a fast-growing tech startup