Agentic Context Engineer

Overview

Agentic Context Engineer within a Field Engineering team, guiding customers from early solution shaping through scaled deployment of WisdomAI's agentic intelligence systems across complex enterprise data landscapes.

What you'll do

• 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 need

• 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.
• 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.

Details

• Location: Remote.