Outreach

• Lead competitive intelligence and market research, translating customer, competitor, and industry insights into differentiated positioning and strategic recommendations. • Serve as the subject matter expert on competitive dynamics, buyer priorities, market trends, and AI innovations, translating insights into battlecards, executive briefs, and enablement programs that improve seller confidence and win rates. • Develop portfolio-level competitive narratives and messaging that clearly articulate Outreach's differentiation. • Lead cross-functional initiatives that strengthen Outreach's competitive position and improve GTM effectiveness. • Influence Product, Marketing, Sales, Customer Success, and executive leaders on competitive priorities and market opportunities. • Act as a trusted advisor to GTM leaders, using data-driven insights to shape go-to-market strategy, content investments, and positioning. • Monitor market shifts, competitive moves, and AI trends to identify opportunities and risks that inform strategy. • Represent Outreach with customers, analysts, and industry audiences as a leader in competitive strategy and market intelligence.

• Retain current customers and identify opportunities to grow or expand their presence and usage across the platform. • Manage the relationship with current customers, including contract renewals and identifying expansion opportunities. • Drive platform adoption and assess overall health of a customer’s engagement with Outreach. • Provide strategic insight and guidance to customers aligned with their goals. • Act as trusted advisors to the Revenue Office for their customers and provide guidance throughout the customer’s journey.

• Experiment, design, implement, and improve machine learning systems. • Contribute to machine learning applications end to end, i.e. from research to prototype to production. • Work with product managers, designers, and customers to define vision and strategy for a given product.

• Own the install base marketing strategy: identify underused features and usage gaps, prioritize which capabilities matter most to each customer segment, and develop messaging and campaigns that drive customer engagement and product adoption. • Create adoption-focused content including in-app messages and email campaigns that drive customer engagement and value realization • Develop internal enablement resources including playbooks and battlecards that equip internal customer success teams for proactive, value focused customer conversations • Gain and develop a deep understanding of new and upcoming product capabilities and assist in the development of customer-facing product communications • Define and track adoption metrics (feature activation rates, usage, time-to-adoption) in collaboration with data and analytics; use insights to evaluate program performance and identify areas for optimization. • Map the customer onboarding journey and develop content for admins, reps, managers, and GTM leaders coordinating with Customer Success (customer success, professional services) and Enablement to keep materials current. • Identify expansion signals and partner with Growth Marketing to run campaigns that reduce churn and support renewals, informed by ongoing customer research (interviews, surveys, usage data). • Partner with Customer Advocacy to identify customers well-positioned to serve as references • Support monthly product launch motion with content creation and customer campaigns that drive adoption • Work with the greater product marketing team on important team projects and events as assigned.

• Process design - with an eye to efficiency; design new and adjust existing customer-centric processes and outcomes in support of continuous improvement • Support organizational Change by rolling out new processes and systems and supervise adoption, both internally and externally to ensure consistency • Analyze positive and negative trends utilizing data from customers, individuals and systems to provide data interpretation • Leveraging data to identify gaps, assess goals and targets, produce gap analysis and promote process & design • Use AI to drive retention and expansion. Design and run AI and agentic workflows, including Claude-based workflows, that catch churn risk early, spot expansion signals, and act on them. • Own the customer lifecycle programs across onboarding, adoption, renewal, and growth, and make them measurably better over time. • Run weekly renewal forecast cadence in partnership with CS leadership. • Build and support the digital and tech-touch strategy that drives adoption and engagement across the customers you cannot reach one to one. • Lead and grow a team, and communicate clearly from the top down, including executive correspondence. • Turn customer data into action through health scoring, early-warning signals, and the metrics that show what is working. • Partner with Customer Success, Product, and Revenue leadership to turn insight into pipeline.

• Becoming and acting as a subject matter expert on the Outreach platform and acting as a trusted advisor to both customers and internal teams • Partner and collaborate with Sales to identify customer and prospect selling tools, business processes, opportunities and risks through in-depth discovery • Helping qualify opportunities through in-depth discovery of customer and prospect business processes in order identify opportunities and risks that need to be addressed during the sales process • Participate in product demonstrations highlighting Outreach's business value • Understanding goals and value propositions for various stakeholders within customer organizations • Ensuring effective communication of customer and prospect pains and requirements to Outreach’s onboarding and implementation teams • Building industry credibility through continuous learning of new sales trends & technology from blogs, podcasts, and other industry publications • Collaborating with Product, Customer Success, and other Outreach teams to build a better company and platform for our customers • Sharing your product and selling knowledge with other Outreach teams, helping them strengthen their own skills, and better support our customers and prospects

• Acting as a strategic advisor to executive stakeholders (CROs, COOs, CTOs, VPs of RevOps, etc.), influencing vision and technical direction for enterprise customers. • Owning the technical strategy for high-value, multi-threaded deals, driving discovery, solution design, and value articulation aligned to customer initiatives. • Leading engaging, outcome-based demonstrations and Proof of Value (POV) engagements that connect Outreach’s capabilities to business outcomes. • Partnering with AEs to craft win strategies using MEDDPICC, Demo2Win, and value-selling frameworks. • Translating complex business processes into scalable, ROI-driven solutions and clearly articulating “the art of the possible” through Outreach’s platform and AI agents (Amplify, Kaia, Research Agent). • Building credibility as a subject matter expert in revenue execution, pipeline management, and AI innovation. • Acting as a mentor and deal coach to Solutions Consultants, providing feedback and guidance on demo execution, discovery, and strategic selling. • Collaborating with Product, Engineering, and Enablement to influence roadmap priorities and build differentiated enterprise narratives. • Creating and maintaining scalable demo and POV assets, vertical playbooks, and industry-specific solution stories. • Representing Outreach as a thought leader through webinars, customer roundtables, and industry events.

• Leading the architecture, design, and delivery of distributed cloud-native applications capable of high concurrency and demanding real-time data needs. • Designing and building production-grade data pipelines and ETL/ELT workflows — modeling data for both transactional (OLTP) and analytical (OLAP) use, and orchestrating them with modern workflow tooling. • Integrating ML and GenAI capabilities into product features — from model serving and evaluation to LLM-powered enrichment, retrieval (RAG), and intelligent automation within our services. • Championing data quality and correctness — building validation, observability, and testing into every step of the pipeline so downstream analytics and AI features can be trusted. • Collaborating with data science, product, and engineering partners to ship intelligent, complex product features. • Setting and promoting engineering standards for code quality, security, and operational excellence; nurturing automation and continuous improvement. • Diagnosing and eliminating performance bottlenecks and proactively addressing reliability risks. • Mentoring, reviewing code/architectures, and fostering a culture of rapid learning. • Decomposing legacy systems into SOA/microservices, resolving tech debt, and evolving the architecture for scale. • Taking end-to-end ownership of major initiatives from planning through impact.

• Knowledge Graph Design & Construction: Architect and evolve per-tenant knowledge graph schemas, including entity resolution, temporal modeling, and ontology design tailored to sales execution domains. • Information Extraction: Architect NLP pipelines that extract structured knowledge from unstructured conversational and document data (sales calls, emails, CRM notes), including coreference resolution, relation extraction, and event detection. • Contextual Reasoning & Recommendation: Design reasoning and inference layers over the knowledge graph to power next-best-action suggestions, deal risk scoring, coaching recommendations, and competitive intelligence surfaces. • Representation Learning: Design and train graph-based models (GNNs, relational embeddings, link prediction) over heterogeneous, multi-relational graph structures to support downstream reasoning and retrieval tasks. Diagnose and address embedding quality issues including cold-start entities, and temporal drift. • Domain Modeling: Formalize sales execution concepts such as deal stages, buyer engagement patterns, rep behaviors, and account health, into structured representations that ground the platform's AI capabilities. Extract ontology structure. Lead ontology versioning and migration. • Cross-functional Collaboration: Partner with engineering, product, and data teams to bring models from prototype to production, ensuring reliability and measurable impact at scale.

• Knowledge Graph Design & Construction: Design and implement entity resolution and ontology population within established graph schemas. Write and optimize queries for graph traversal and feature extraction. Own data quality for assigned domains. • Information Extraction: Build pipelines that extract structured knowledge from unstructured conversational and document data (sales calls, emails, CRM notes), including coreference resolution, relation extraction, and event detection. Run experiments to compare approaches and improve accuracy metrics. • Contextual Reasoning & Recommendation: Implement graph traversal logic and feature queries that feed downstream scoring signals. Build and maintain features for deal risk, next-best-action, or coaching recommendation surfaces. • Representation Learning: Train and evaluate link prediction and node classification models using established graph embedding methods. Implement evaluation pipelines and track model performance over time. • Domain Modeling: Translate sales concepts, such as deal stages, buyer engagement patterns, rep behaviors, and account health, into graph nodes and relationships under the guidance of senior scientists. Contribute to ontology design and documentation. • Cross-functional Collaboration: Work with software engineers to deploy models and pipelines into production. Write clean, tested code. Monitor system health and respond to incidents. Participate in code review and design discussions.