The Role: As an Agentic Context Engineer at WisdomAI, you will work within a Field Engineering team to guide customers from early solution shaping through scaled deployment. You will help operationalize WisdomAI across complex enterprise data landscapes, turning fragmented data into production-grade agentic intelligence systems that power automated, insight-to-action workflows.
This is a hands-on role for builders who love shipping real systems and owning outcomes end to end.
Core Responsibilities- Drive technical pre-sales engagements: Partner with Sales to lead technical discovery, customer workshops, solution architecture, POCs, and evaluations, translating business challenges into high-value use cases and technical wins.
- Own initial post-sales implementation: Lead technical execution from deal closure through initial production deployment, including data onboarding, context modeling, validation, user enablement, and structured handoff.
- Engineer enterprise AI solutions: Design and build scalable context and semantic models, agentic workflows, and integrations across complex enterprise data environments.
- Solve complex enterprise technical challenges: Work with customer data, IT, and security teams to address integration, performance, governance, security, and scalability requirements.
- Develop reusable engineering assets: Build context models, certified demos, solution patterns, and deployment playbooks that accelerate customer engagements and improve engineering efficiency.
- Influence product evolution: Partner with Product and Engineering to translate customer requirements, technical gaps, and field learnings into scalable platform capabilities.
- Serve as a trusted technical advisor to customer architects, data leaders, and executive stakeholders
What You'll Bring: QualificationsExperience & Background- 10+ years of experience in enterprise data, AI/ML, solutions engineering, or technical consulting, with a focus 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
- Strong technical foundation in data architectures, data modeling, and scalable AI/analytics solutions, with experience navigating complex environments.
- Excellent communication and stakeholder management skills, with the ability to engage technical and executive audiences and translate technology into business value.
- High ownership mindset with a focus on real outcomes
Technical Expertise- 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
Why Join Wisdom AI?- Work at the cutting edge of Generative AI and Enterprise Data
- High autonomy in a flat organization where your work directly impacts the product roadmap and overall company success
- Opportunity to work with a world-class engineering team from the most successful tech companies in the world
Our CRAFTCRAFT isn't a list of aspirational values. It's how we hire, how we promote, how we resolve hard calls, and how we stay honest with ourselves.
C - Customer trust. Everything starts here. We listen carefully, act with integrity, and respond with urgency. Delight is downstream of trust - never the other way around.
R - Relentless on outcomes. We move with urgency, take initiative, and see things through. Effort isn't the measure - results are. If something isn't working, we change the approach now.
A - Authenticity. We say the hard things, directly and with respect. We also show up as full humans. That combination is how trust is earned and how we grow together.
F - First principles, grounded in reality. We don't accept "that's how it's done." We strip problems to what's actually true and build up from there - then validate quickly and let real-world results decide.
T - Transparency. We share the why, not just the what. When something can't be shared, we say so. We're one team - information flows so we can do our best work and challenge each other when we're wrong.
