Job Title: AI Pricing Applied Engineer
Location: Santa Clara, 5x onsite
Duration: 9 months
Job Description:
As an AI Pricing Applied Engineer (Contract), you'll work alongside the WWFO Enterprise Pricing team to transform pricing, rebate, and quoting operations through practical AI-driven solutions. Our focus is on reducing manual operational overhead, improving accuracy, and enabling scalable, intelligent decision-making across enterprise pricing systems.
This role is ideal for someone who thrives at the intersection of AI and real-world business applications—someone who can quickly move from identifying inefficiencies to building and deploying solutions that drive measurable impact. You’ll work across platforms like Salesforce, SAP, Vistex, and modern data environments to embed AI directly into pricing workflows.
We’re looking for a builder—someone who is hands-on, proactive, and comfortable operating in ambiguity while delivering high-impact outcomes.
What you’ll be doing:
- Drive execution of the Pricing AI roadmap by assessing current pricing, rebate, and quoting processes and identifying high-impact automation opportunities
- Build AI agents that proactively monitor pricing data and detect anomalies using data from Salesforce, SAP, Vistex, and analytics platforms
- Develop AI-enabled workflows that automate manual processes across rebate review, policy validation, price list generation, and pricing execution
- Design and implement AI-powered tools that improve productivity for pricing and cross-functional WWFO teams by simplifying access to insights and operational data
- Architect scalable AI solutions and infrastructure that support price-sensitive and confidential data with appropriate governance and controls
- Partner with pricing, business, and sales stakeholders to translate operational pain points into deployable AI solutions
- Serve as an AI thought partner by introducing emerging tools and driving adoption of AI capabilities across pricing use cases
What we need to see:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
- Proven experience building and deploying applied AI/ML solutions in production, ideally in business operations or enterprise systems
- Strong Python skills and experience working with modern AI tools (e.g., LLM APIs, LangChain, vector databases, ML frameworks)
- Experience integrating and working with enterprise systems such as Salesforce, SAP, or similar platforms
- Strong SQL and data engineering fundamentals, including working with large and complex datasets
- Experience building data pipelines and working with cloud data platforms (e.g., Databricks, BigQuery, Snowflake)
- Strong problem-solving skills with the ability to operate independently and drive end-to-end execution
Ways to stand out from the crowd:
- Experience building AI agents/copilots that automate operational workflows
- Hands-on experience applying LLMs to enterprise use cases (e.g., decision support, anomaly detection, document automation)
- Familiarity with pricing, rebate systems, CPQ platforms, or financial operations
- Experience designing AI solutions for sensitive or regulated data environments
- Track record of delivering practical, production-ready solutions (not just prototypes)
- Passion for rapidly learning and applying emerging AI technologies to real business problems
