Forward Deployed Engineer
- Role
- AI / ML
- Employment
- Full-time
- Company size
- Startup
Open to UTC-8…UTC-5. Set where you work from to check your eligibility.
No BS summary
Customer-facing Forward Deployed Engineer for US enterprise deployments of agentic AI solutions. Needs hands-on experience with LLM agents, prompt engineering, RAG, orchestration, APIs/integrations, and Python or JavaScript/TypeScript. Must work United States timezones and be comfortable with enterprise stakeholders from evaluation through production deployment.
Core skills
Required skills
Optional skills
BUILD THE FUTURE WORKFORCE
Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. And it’s already operating at scale inside some of the world’s largest organizations.
Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.
Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy. We’re building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale.
JOIN WAND IN LEADING THE AGENTIC SHIFT
Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers.
You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern.
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’ll work closely with customers to understand their business needs, identify high-value use cases, design and build agentic solutions, configure and integrate Wand into their environment, and present working solutions that clearly demonstrate business impact.
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. This is a builder’s role in a fast-moving startup: you’ll operate with minimal hand-holding, bring structure to ambiguous customer problems, and own the technical path to value.
WHAT YOU'LL DO
- 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.
- Translate customer needs into clear solution designs, agent architectures, workflow logic, integration specs, and deployment plans.
- Present technical solutions, demos, prototypes, and deployment plans to customer stakeholders, including technical teams, business leaders, and executives.
- Troubleshoot across APIs, authentication, data, workflow logic, agent behavior, and customer systems.
- 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.
WHAT WE'RE LOOKING FOR
- 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.
- Strong experience building agents, agentic workflows, LLM-powered applications, or AI automation solutions.
- 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.
- Strong hands-on skills with APIs, integrations, scripting, debugging, and cloud/web environments.
- Coding or scripting ability in Python, JavaScript/TypeScript, or similar.
- Ability to build quickly, demo effectively, and iterate based on customer feedback.
- Clear communication with both technical and non-technical audiences.
- High ownership: you drive customer outcomes, unblock yourself, and move fast without waiting for perfect instructions.
- Comfort with ambiguity and shifting priorities in an early-stage, high-growth environment.
PREFERRED EXPERIENCE
- Experience deploying AI, agentic, automation, or enterprise SaaS products into production environments.
- Experience building customer-facing demos, prototypes, or proof-of-value solutions.
- 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.
- Experience working with regulated industries or enterprise customers with complex security and compliance needs.
- Prior startup experience in an early-stage or high-growth setting.
WHO THRIVES HERE
Builders who can sit with a customer, understand the real problem, quickly build an agentic solution, and present it clearly enough that the customer immediately sees the value.
You’ll thrive here if you are technical, customer-facing, fast-moving, and independent. You prototype and debug rather than only coordinate. You take responsibility for the customer outcome, communicate proactively, flag risks early, and follow through. You are comfortable being the technical adult in the room, whether you’re speaking with a customer’s security architect, operations lead, engineering team, or COO.
We’re looking for someone low-ego, collaborative, sharp, and highly accountable — someone who can build trust with customers while also building real technical solutions.
What you'll do
- 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.
- Translate customer needs into clear solution designs, agent architectures, workflow logic, integration specs, and deployment plans.
- Present technical solutions, demos, prototypes, and deployment plans to customer stakeholders, including technical teams, business leaders, and executives.
- Troubleshoot across APIs, authentication, data, workflow logic, agent behavior, and customer systems.
- 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.
What they require
- 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.
- Strong experience building agents, agentic workflows, LLM-powered applications, or AI automation solutions.
- 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.
- Strong hands-on skills with APIs, integrations, scripting, debugging, and cloud/web environments.
- Coding or scripting ability in Python, JavaScript/TypeScript, or similar.
- Ability to build quickly, demo effectively, and iterate based on customer feedback.
- Clear communication with both technical and non-technical audiences.
- High ownership: drive customer outcomes, unblock yourself, and move fast without waiting for perfect instructions.
- Comfort with ambiguity and shifting priorities in an early-stage, high-growth environment.
- Preferred: Experience deploying AI, agentic, automation, or enterprise SaaS products into production environments.
- Preferred: Experience building customer-facing demos, prototypes, or proof-of-value solutions.
- Preferred: Experience working in pre-sales, post-sales, implementation, or field engineering environments.
- Preferred: Integration experience with REST APIs, webhooks, OAuth, JWT, mTLS, and third-party enterprise systems.
- Preferred: Experience with VPC or on-prem deployments, cloud infrastructure, containers, databases, logs, and production troubleshooting.
- Preferred: Familiarity with enterprise security, data privacy, RBAC, audit, governance, and compliance requirements.
- Preferred: Experience working with regulated industries or enterprise customers with complex security and compliance needs.
- Preferred: Prior startup experience in an early-stage or high-growth setting.
- Comfort speaking with technical and executive stakeholders.
- Ability to move quickly from problem discovery to prototype.
- Ability to turn complex workflows into production-ready agents and multi-agent systems.
- Ability to operate with minimal hand-holding, bring structure to ambiguous customer problems, and own the technical path to value.
- Low-ego, collaborative, sharp, and highly accountable.
- Ability to build trust with customers while building real technical solutions.
Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.