Agentic Context Engineer

WisdomAI builds AI-powered analytics that help businesses turn enterprise data into actionable insights. The Agentic Context Engineer guides customers from solution shaping through scaled deployment by designing, implementing, and operationalizing enterprise AI systems and workflows.

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

Requirements:

• 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