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WisdomAI is an AI-powered analytics platform that helps enterprises unlock insights from complex data. The company is trusted by organizations like Cisco, Patreon, and Rubrik, and is backed by Tier-1 VCs with a team of founding engineers and leaders from Google, Meta, AWS, Rubrik, and Glean.
As an Agentic Context Engineer, you will work within a Field Engineering pod to guide strategic customers from early solution shaping through scaled deployment. This is a hands-on role for builders who love shipping real systems and owning outcomes end-to-end.
Core Responsibilities:
- Drive large, complex sales opportunities from ideation through vision building, scoping, closure, and into delivery
- Conduct workshop sessions to identify customer opportunities and scope business value delivery with WisdomAI
- Own the holistic health and ROI of your customer portfolio, identifying "North Star" use cases that move the needle for their business
- Own post-sale technical execution for strategic customers through deployment and scale
- Design and ship enterprise context layers that turn fragmented enterprise data into production-ready agent-driven workflows
- Lead complex technical problem-solving across data integration, performance, governance, and security domains
- Build reusable context models, solution patterns, and deployment frameworks
- Partner with Product and Engineering to shape platform evolution by translating customer needs into scalable product capabilities
- Serve as a trusted technical advisor to customer architects, data leaders, and executive stakeholders
The role offers high autonomy in a flat organization where your work directly impacts the product roadmap and overall company success. You'll work at the cutting edge of Generative AI and Enterprise Data alongside a world-class engineering team.
Requirements:
- 10+ years of experience combining deep technical expertise in data/AI/ML platforms consulting or delivery leadership focused on business impact
- Bachelor's or Master's in Engineering, Data, or a related field, or equivalent experience
- Experience working across both customer-facing pre-sales and post-sales engagements
- Proven track record deploying complex platforms into production enterprise environments
- Deep understanding of enterprise data modeling, context/semantic layers, and system scalability
- Clear communication skills to engage engineers, architects, and executives
- High ownership mindset with focus on real outcomes
- Hands-on experience with modern analytics and cloud data platforms, including semantic and metadata layers
- Advanced SQL and strong Python proficiency for data transformation, orchestration, and automation
- Understanding of how Generative AI works, including prompt engineering, RAG (Retrieval-Augmented Generation), and evaluation sets
- Familiarity with data governance, security, access controls, and performance optimization in enterprise environments
