Wand AI

Sales Engineer

• Lead technical pre-sales engagements — partner with Sales and Product to architect high-impact solutions that align with client goals, data realities, and Wand’s differentiators.
• Design and deliver lightweight, believable prototypes that prove Wand’s unique capabilities — from legal document parsing to agentic workflow automation.
• Own the “Proof-to-Contract” motion — help clients define what must be proven technically (accuracy, scalability, adaptability) to justify commercial commitment.
• Act as a consultative discovery partner — uncover what customers really need, not just what they ask for, and reframe “fishing expedition” demos into contract-worthy hypotheses.
• Build reusable demo systems and technical frameworks that make it faster for the next SE to spin up an environment, run a workflow, or connect a customer dataset.
• Contribute Python scripts, API workflows, and reference architectures that showcase best practices for integrating Wand into client ecosystems.
• Mentor and scale a small, high-performing team of Sales Engineers — establishing standards for demo quality, engagement discipline, and technical storytelling.
• Collaborate cross-functionally with Product and Engineering to channel field feedback into roadmap priorities and product enablement.
• Develop and document playbooks — from demo readiness and proof scoping to customer engineering rituals — building the foundation for a repeatable SE function.
• Represent Wand externally — lead workshops, client sessions, and conference demos that position Wand as the most capable, credible applied AI partner in the market.

• Lead technical pre-sales engagements
• Partner with Sales and Product to architect high-impact solutions
• Design and deliver lightweight, believable prototypes
• Own the “Proof-to-Contract” motion
• Act as a consultative discovery partner
• Build reusable demo systems and technical frameworks
• Contribute Python scripts, API workflows, and reference architectures
• Mentor and scale a small, high-performing team of Sales Engineers
• Collaborate cross-functionally with Product and Engineering
• Develop and document playbooks
• Represent Wand externally

Sales Engineering Manager

Founding Sales Engineering Manager

QA Engineer

• Develop and maintain comprehensive test strategies across backend services, APIs, and data pipelines.
• Build, maintain, and improve test automation frameworks (integration, regression, E2E, performance).
• Perform manual testing to validate new features, edge cases, and user scenarios.
• Identify, isolate, and document bugs thoroughly—work closely with engineers to resolve them.
• Collaborate with developers during planning and design to establish clear acceptance criteria and test coverage.
• Define quality metrics and implement monitoring to track and improve software reliability over time.
• Ensure cross-environment stability (dev/staging/prod) and proactively identify regressions or side effects.
• Participate in release and deployment processes to ensure only well-tested code goes live.
• Advocate for a quality-first culture and mentor other engineers on testing best practices.

AI Research Scientist

• Wand AI’s mission is to drive a generational leap for the global economy by integrating agent ecosystems into the core of work, business, and society.
• Join AI’s brightest minds and work with top talent from DeepMind, Microsoft Research, Google Brain, Amazon, Nvidia, IBM, Jasper, and Hubspot.
• Focused on outcomes; elite global team; high ownership, and aggressive timelines to shape the future.
• Responsibilities: Design, build, and ship end-to-end AI prototypes and features with a high sense of urgency.
• Own the entire development lifecycle: from understanding a vague problem statement to producing clean, scalable, production-level code.
• Rapidly survey, select, and implement state-of-the-art models and techniques to solve immediate business problems.
• Work independently to architect and build robust systems, making pragmatic trade-offs between perfection and speed.
• Quickly ramp up on new domains, frameworks, and technologies as needed to get the job done.
• Focus on tangible outcomes and delivering working features to customers; reports and papers are a by-product, not the goal.

AI Researcher

Backend Engineer

• Develop and maintain backend services supporting AI features and business logic
• Collaborate closely with AI researchers, product managers, and frontend engineers
• Implement clean, maintainable, and testable code
• Optimize APIs and data processing pipelines for performance and scalability
• Participate in code reviews, design discussions, and team meetings
• Stay up to date with industry best practices in backend and AI integration

AI-focused Backend Engineer

Full-stack Engineer

• Design, build, and maintain scalable data pipelines and systems that support agentic applications.
• Develop backend services and APIs that handle data ingestion, transformation, and access.
• Work closely with the Data Engineering lead to define architecture and technical direction.
• Integrate structured and unstructured data sources into agent workflows.
• Ensure high performance and reliability of data systems in production environments.
• Collaborate with AI researchers and product teams to deliver intelligent, data-driven features.
• Contribute to best practices in data governance, quality, and security.

Data Experience Software Engineer @ Wand Synthesis AI Inc.

Product Designer

• Conduct in-depth user research through interviews, surveys, usability testing, and data analysis.
• Map and analyze end-to-end user journeys to identify friction points and opportunities.
• Zoom into critical interaction points such as how a user completes a single action or interprets a single screen and refine usability at the micro level for maximum clarity and efficiency.
• Create user personas, journey maps, user flows, wireframes, and prototypes to communicate design intent.
• Collaborate closely with product managers, designers, and developers to translate insights into product improvements.
• Advocate for UX best practices and user-centered design across the organization.
• Ensure consistency and accessibility across all digital touchpoints.
• Continuously test, measure, and refine design solutions based on user feedback and data.