• Build and execute a company-wide AI adoption strategy • Design role-based enablement programs • Stand up and scale an internal AI Champions network • Create communication strategies that demystify AI • Develop and track adoption metrics

• Prototype Incubation & Auditing: Evaluate "vibe-coded" AI tools and automations built by non-technical business units (StratOps, Commercial Ops, etc.) to help boost their commercial ROI, security posture, and architectural viability. • Production Refactoring (The Paved Road): Take ownership of high-value internal prototypes (e.g., AI SDRs, RFP generators) and refactor them into secure, scalable, and enterprise-grade applications. • LLM Orchestration & Integration: Build and maintain secure integrations between foundational models (via APIs) and Impiricus's internal systems, specifically our Enterprise Data Lake and CRM (Salesforce). • Full-Lifecycle Maintenance: Act as the technical owner for all "graduated" internal AI applications, ensuring high uptime, managing prompt drift, and updating API connections as internal schemas change. • Cross-Functional Product Management: Act as your own PM. Interview business stakeholders to map complex operational bottlenecks, ruthlessly define scope, and manage stakeholder expectations regarding what should be an AI experience versus a standard SQL dashboard. • Governance Enforcement: Apply Enterprise Data & Analytics standards to all internal tooling, ensuring zero data leakage, strict access controls, and mitigation of hallucination risks in operational outputs.

Role Description Glean is seeking a talented AI Outcomes Manager to join our rapidly expanding team. The AI Outcomes Manager will play a crucial role in transforming how every department works, with the power of Glean. You will: - Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean. - Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform. - Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities. - Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform. - Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. - Proactively identify expansion opportunities and drive engagement across teams and functions. Qualifications - 5+ years of professional experience in roles that blend business and technology (e.g., product, analytics, data, engineering, solutions), with a consultative, customer‑facing approach. - Strong problem‑solving and communication skills; comfortable working with stakeholders from ICs to executives and tailoring messages to different audiences. - Demonstrated ability to craft effective prompts and guide AI agents for real customer or business workflows; you’ve shipped outcomes, not just demos. - Understanding of what current LLMs can and cannot do; able to set expectations and steer towards reliable, safe, cost‑effective solutions. - Product sense and user empathy—you can spot high‑value applications of AI across diverse job functions and design clear, guided experiences. - Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar), with enough technical depth to work with engineers without needing to be on the critical path for writing production code. - Fluent in English and Portuguese. Requirements - Prior experience in customer‑facing, consultative roles (solutions, support, product management) and comfort presenting to senior leaders. - Exposure to evaluating AI outcomes (e.g., defining success criteria, using sample tasks, reviewing results) and iterating for quality, latency, and cost. - Ability to analyze usage signals and customer feedback to inform roadmap and drive adoption. Location This role is remote (must be based in Brazil). Compensation & Benefits Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. AI-First Mindset at Glean At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.

• Own the AI technology strategy, architecture, and execution for a small, highly technical startup • Report directly to the CTO • Build, ship, and scale applied AI in a company where the work is central to product success • Define and execute the technical AI roadmap • Deliver technical, product, and operational outcomes tightly aligned with company goals • Hire, mentor, and manage a small team of senior generative AI engineers • Partner closely with Product Management and Project Management • Lead architecture and implementation for core AI systems, including: LLM-based workflows, RAG systems, AI agents, Evaluation and testing systems, Observability and performance monitoring, Model selection and routing, Data ingestion and retrieval systems • Own major parts of the company’s data ingestion pipeline into platform storage and analytics systems • Build infrastructure to host LLMs in the company’s new data center environment • Establish strong experimentation and measurement practices for AI features • Serve as an internal evangelist for effective use of AI agents inside the engineering organization