Wand AI
Forward Deployed Engineer
United States Timezone
Sponsorship not specifiedDetected 17 days ago
JavaScriptTypeScriptPythonCloud PlatformsRESTOAuthLLMsRAGAgentic AILangGraphCybersecurityResearchCommunication
> stay_score
odds of building a lasting career here
16Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
No strong sponsorship signal in the public record yet. In the full product we resolve the exact legal entity and show its filing history with a confidence score — treat as unverified until then.
Lottery odds assume a STEM candidate.
Personalize to your clock →> community_outcomes
No reports yet — be the first to help the next applicant.
About the role
- We're hiring a hands-on Forward Deployed Engineer to work directly with enterprise customers and help them see value from Wand AI quickly from evaluation through production deployment.
- This is a highly customer-facing role at the intersection of engineering, solution architecture, agentic AI, and customer delivery.
- You should be comfortable speaking with both technical and executive stakeholders, moving quickly from problem discovery to prototype, and turning complex workflows into production-ready agents and multi-agent systems.
Responsibilities
- Translate customer needs into clear solution designs, agent architectures, workflow logic, integration specs, and deployment plans.
- Support late-stage pre-sales when solution design, technical feasibility, implementation planning, or customer value demonstration is critical.
- Create implementation playbooks, solution patterns, demo flows, and deployment documentation that make future deployments faster.
- Strong experience building agents, agentic workflows, LLM-powered applications, or AI automation solutions.
Requirements
- Demonstrated hands-on experience in a customer-facing technical role such as Forward Deployed Engineer, Solutions Engineer, AI Engineer, Implementation Engineer, Solutions Architect, Technical Consultant, or similar.
- Ability to understand customer needs quickly and translate them into working technical solutions, not just documentation or coordination plans.
- Strong practical experience with LLMs, prompt engineering, tool-calling, RAG, orchestration, multi-agent workflows, evaluation, and agent behavior debugging.
- Experience with frameworks or tools such as LangGraph, LangChain, CrewAI, or similar agentic/LLM development frameworks.
- Comfort with ambiguity and shifting priorities in an early-stage, high-growth environment.
Nice to have
- Experience deploying AI, agentic, automation, or enterprise SaaS products into production environments.
- Experience working in pre-sales, post-sales, implementation, or field engineering environments.
- Integration experience with REST APIs, webhooks, OAuth, JWT, mTLS, and third-party enterprise systems.
- Experience with VPC or on-prem deployments, cloud infrastructure, containers, databases, logs, and production troubleshooting.
- Familiarity with enterprise security, data privacy, RBAC, audit, governance, and compliance requirements.
- Prior startup experience in an early-stage or high-growth setting.
Company info
- Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy.
- ABOUT THE ROLE We're hiring a hands-on Forward Deployed Engineer to work directly with enterprise customers and help them see value from Wand AI quickly from evaluation through production deployment.
- Work directly with enterprise customers to understand their business needs, operational workflows, pain points, and success criteria.
- Design, build, and present agentic solutions, prototypes, and workflows that demonstrate value to customers.
- Own end-to-end technical deployments of Wand for US enterprise customers, from evaluation and solution design through production go-live.
Apply directly at Wand AI →Create a free account for alerts like thisView Wand AI immigration profile
This listing is sourced directly from Wand AI's careers page and normalized into a canonical job model.