Forward Deployed Engineer
About The Position
The company is building critical infrastructure to enable AI models to take real actions in the real world, moving beyond chat-only capabilities. They are creating a definitive tools catalog and tool-calling platform, envisioned as "Zapier for AI actions" or "Auth0 for AI." The Forward Deployed Engineer role is pivotal, involving inspiring sophisticated AI teams, designing custom prototypes and reference architectures, and acting as a trusted consultant to guide customers in transitioning from passive chat to active, automated intelligence. This position demands deep technical expertise, exceptional articulation skills, and an insatiable curiosity to master the rapidly evolving Agentic AI ecosystem, including LLM orchestration, autonomous agent frameworks, and tool-calling infrastructure. The company highlights its strong leadership, experienced team from top tech companies, perfect timing in the AI market, massive market potential, and backing by prominent investors in the data and AI space.
Requirements
- Deep Integration DNA: Experience connecting enterprise systems in any form, including 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 understand the "why" and business impact of solutions and explain high-level concepts to executive buyers without losing technical detail.
- Evangelist Mindset: Willing presenter, excited to speak at conferences, and interested in creating technical content and blogs to lead the agentic AI conversation.
- AI-Forward Mindset: Actively uses AI in daily workflows and eager to master the agentic landscape.
- AI Agent Builder: Experience building with LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar, and understanding the challenges of giving agents real-world capability.
- Backend Engineer: Shipped production microservices and understands what it takes to run, observe, and scale distributed systems.
- Identity & Security Practitioner: Deep fluency in OAuth 2.0, OIDC, SAML, SCIM, token lifecycles, delegated auth, and the modern identity stack.
- Infrastructure Engineer: Experience with Kubernetes, containers, service meshes, cloud platforms (AWS/GCP/Azure), and CI/CD pipelines, and knowledge of enterprise software deployment.
Nice To Haves
- Meaningful work in data science, ML engineering, or applied AI/ML.
Responsibilities
- Act as the Technical Authority: Partner with AEs to lead technical discovery and evaluations with Head of AI, CTO, and Architect personas.
- Build the "Art of the Possible": Design and build custom prototypes, PoCs, and reference architectures that show exactly how our infrastructure enables real-world AI actions.
- Simplify the Complex: Take abstract infrastructure, middleware, and API concepts and turn them into clear, value-driven solutions for customers.
- Field-to-Product Loop: Act as the eyes and ears of the market, funneling deep technical feedback back to our Product and Engineering teams to shape the roadmap.
- Empowered to take customer learnings to create working prototypes and systems that can eventually become part of the core platform.
- Drive Technical Wins: Navigate complex technical hurdles in deal cycles ranging from $200K+ to seven figures.
- Master the AI Stack: Stay at the bleeding edge of the ecosystem (LangChain, LlamaIndex, Vector DBs) to consult customers on their broader AI strategy.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
11-50 employees
