AI Sales Intelligence Analyst

F5 Networks•Seattle, WA

8d•Hybrid

About The Position

We're looking for a builder-minded analytics professional to join F5's Sales Business Intelligence team and help develop AI-powered analytics experiences for our global sales organization. This role sits at the intersection of data engineering, applied AI, and sales operations — and, equally important, at the intersection of the many partner teams that make sales intelligence possible. You will spend as much time listening to sales leaders, account teams, and cross-functional partners as you do writing code: translating ambiguous business questions into well-scoped agents, semantic models, and data products, and then clearly explaining what these systems can and cannot do. You will help design, build, and maintain conversational analytics agents that allow sales leadership and executives to interrogate revenue, pipeline, and territory data in natural language. You will contribute to new agent builds and integrations — connecting our SharePoint, Salesforce, Snowflake, and Databricks ecosystems into a unified sales intelligence layer using modern enterprise AI platforms, agent frameworks, and related tooling. This is a strong opportunity for an early-career analyst or engineer who combines hands-on AI/LLM experience with strong communication and collaboration instincts.

Requirements

Communication Excellence: Strong written and verbal communication skills, with the ability to convey complex technical AI concepts in clear, concise language for non-technical audiences.
Comfort presenting work, demos, and findings to peers, senior stakeholders, and on occasion executive leadership.
Ability to produce clear documentation, enablement materials, and user-facing written communications.
Collaboration and Partnership: Exceptional collaboration instincts, with the ability to build trusted working relationships across sales, operations, finance, IT, and engineering functions.
Strong listener — able to sit with ambiguous business problems, ask good questions, and translate what they hear into concrete technical scope.
Comfortable working under time constraints and iterating on ambiguous problems with guidance from more senior team members.
Applied AI and Agent Building: Hands-on experience building with LLMs, including prompt engineering, tool use / function calling, and retrieval-augmented generation — in a professional, academic, or substantive personal project setting.
Exposure to at least one agent framework such as Google's Agent Development Kit (ADK), LangGraph, LangChain, Vertex AI Agent Builder, or Snowflake Cortex Agents.
Working understanding of enterprise AI and data governance concepts — including access controls, PII handling, and responsible AI practices — or a clear eagerness to learn.
Data and Technical Proficiency: Solid SQL skills and working experience with a cloud data warehouse such as Snowflake, BigQuery, or Databricks.
Proficiency in Python for data work and API integrations; familiarity with full-stack development (FastAPI, Next.js, or similar) is a plus.
Familiarity with at least one major cloud platform: Google Cloud (Vertex AI, BigQuery) or Microsoft Azure (Azure AD, Key Vault, Logic Apps).
Experience working with CRM or enterprise business data, such as Salesforce opportunity, forecasting, or territory data, is a plus.
Experience with a data visualization tool such as Tableau, Power BI, or Looker, and an eye for clear, accurate presentation of data.
Experienced in Microsoft Office and collaborative tools (SharePoint, Teams).
BA/BS degree in Computer Science, Data Science, Statistics, Finance, Business Administration, or a related field; coursework or academic projects in AI, machine learning, or applied LLM systems is a strong plus.
2–3 years of professional experience in data analytics, data engineering, analytics engineering, or applied AI/ML; equivalent combinations of relevant coursework, research, internships, or substantial personal projects on AI systems will also be considered.
Any hands-on experience building LLM or agent-based applications — professional, academic, or personal — is strongly preferred.
Experience supporting a sales, revenue operations, or comparable GTM organization is a plus, not a requirement.

Nice To Haves

Familiarity with full-stack development (FastAPI, Next.js, or similar) is a plus.
Experience working with CRM or enterprise business data, such as Salesforce opportunity, forecasting, or territory data, is a plus.
Experience with a data visualization tool such as Tableau, Power BI, or Looker, and an eye for clear, accurate presentation of data.
Coursework or academic projects in AI, machine learning, or applied LLM systems is a strong plus.
Equivalent combinations of relevant coursework, research, internships, or substantial personal projects on AI systems will also be considered.
Any hands-on experience building LLM or agent-based applications — professional, academic, or personal — is strongly preferred.
Experience supporting a sales, revenue operations, or comparable GTM organization is a plus, not a requirement.

Responsibilities

Partner with Sales and Cross-Functional Teams: Serve as a trusted, approachable partner to Sales Operations, Finance, IT, and Sales Leadership — listening carefully to business questions and translating them into well-scoped agents, tools, and semantic model extensions.
Run working sessions, demos, and user feedback loops with sales users to shape AI products that actually get adopted.
Build executive-ready written materials, talking points, and demo narratives that explain complex AI systems in clear, non-technical language.
Build and Maintain AI-Powered Sales Intelligence: Build and maintain conversational AI agents that answer sales, pipeline, bookings, discounting, and territory questions for the global sales organization.
Contribute to new agent builds and support integrations between enterprise AI platforms and our SharePoint, Salesforce, Snowflake, and Databricks systems.
Develop agent components using modern agent frameworks such as the Agent Development Kit (ADK), including specialized analyst sub-agents, tools, and connectors to BigQuery, Snowflake, and Salesforce data.
Author and iterate on YAML semantic models, retrieval pipelines, and vector search indexes that ground agent responses in trusted, governed sales data.
Build and maintain data pipelines in Snowflake, Databricks, and BigQuery that feed agent tools, embeddings, and evaluation datasets.
Ensure Quality, Governance, and Adoption: Contribute to evaluation of agent quality, routing accuracy, and response faithfulness, including building and maintaining regression test cases.
Collaborate with IT and Security teams to support security reviews, threat modeling inputs, and production deployment of AI applications.
Help enable sales users on new AI tools through documentation, onboarding sessions, office hours, and day-to-day user support.
Bring awareness to data quality, integrity, and accessibility issues and support efforts to resolve them.
Uphold F5's Business Code of Ethics and promptly report violations of the Code or other company policies.
Perform additional duties as assigned.