Forward Deployed Engineer

Arcade

36d

About The Position

We are building the infrastructure that will power every AI application in the future, specifically focusing on creating agentic 'tools' that allow AI models to take real-world actions. This role is crucial for enabling AI's true potential by building a definitive tools catalog and tool-calling platform, akin to Zapier for AI actions or Auth0 for AI. The company boasts strong leadership with prior successful exits (Stormpath acquired by Okta), experienced technical leadership from Redis and LangChain/LlamaIndex contributors, and a sales leader from MongoDB. The team comprises experts from leading tech companies, and the timing is opportune due to the current inflection point of AI adoption where connecting AI to real-world actions is the primary challenge. The market is massive, as this infrastructure is critical for every AI application. The company is backed by prominent investors who have supported major tech companies.

Requirements

3+ years of experience as a Pre-Sales/Solutions Engineer, Solutions Architect, or technical consultant who has sold highly technical infrastructure (Databases, Security, Integration, or Cloud), or an engineer ready to pivot into FDE.
Deep Integration & Systems Architecture Fluency: Experience connecting enterprise systems via iPaaS (MuleSoft, Workato, Boomi), ETL/ELT (Informatica, Fivetran, Airbyte), RPA (UiPath, Automation Anywhere), or API gateways and service mesh (Apigee, Kong, Istio).
Hands-on Technical Chops: Comfortable with APIs, SDKs, and coding in modern languages (Python, JavaScript/TypeScript, etc.).
Curiosity & Business Acumen: Ability to dig deep to understand the 'why' and business impact of a solution, and explain high-level concepts to executive buyers without losing the technical plot.
Evangelist Mindset: Willingness to present, speak at conferences, and create technical content and blogs.
AI-Forward Mindset: Actively use AI in daily workflows and eagerness to master the agentic landscape.
Experience with LLM orchestration, autonomous agent frameworks, and tool-calling/action-oriented infrastructure.

Nice To Haves

Built with LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar, and experienced the pain of giving agents real-world capability.
Shipped production microservices and understand running, observing, and scaling distributed systems.
Deep fluency in OAuth 2.0, OIDC, SAML, SCIM, token lifecycles, delegated auth, and the modern identity stack.
Experience with Kubernetes, containers, service meshes, cloud platforms (AWS/GCP/Azure), and CI/CD pipelines.
Meaningful work in data science, ML engineering, or applied AI/ML.

Responsibilities

Act as the Technical Authority, partnering with AEs to lead technical discovery and evaluations with Head of AI, CTO, and Architect personas.
Build the 'Art of the Possible' by designing and building custom prototypes, PoCs, and reference architectures that demonstrate how the infrastructure enables real-world AI actions.
Simplify complex abstract infrastructure, middleware, and API concepts into clear, value-driven solutions for customers.
Act as the market's eyes and ears, funneling deep technical feedback to Product and Engineering teams to shape the roadmap.
Empowered to make feature or fix changes to unblock deployments, and create working prototypes from customer learnings that can become part of the core platform.
Drive Technical Wins by navigating complex technical hurdles in deal cycles ranging from $200K+ to seven figures.
Master the AI Stack by staying at the bleeding edge of the ecosystem (LangChain, LlamaIndex, Vector DBs) to consult customers on their broader AI strategy.
Design architectures that survive rigorous security reviews.
Stay three steps ahead of the rapidly evolving Agentic AI ecosystem, mastering LLM orchestration, autonomous agent frameworks, and tool-calling/action-oriented infrastructure.
Serve as a trusted consultant helping customers architect the transition from passive chat to active, automated intelligence.