Role Overview
As a Field Development Engineer at ai&, you are the most technical person in the customer relationship. You combine deep platform knowledge with the ability to go into any enterprise environment, understand what they are trying to build, and architect the solution that gets them there on ai& infrastructure.
You will work with the most technically demanding customers we have, enterprises deploying AI at scale, startups pushing the boundaries of what agents can do, and engineering teams that need a peer-level technical partner, not a salesperson. You will own the solution architecture end to end: understanding the customer's stack, designing the integration, driving deployment, and staying close through production. You will also build a distributed inference and compute architecture with a customer's ML team and sitting down with their platform engineers to debug a latency issue in the serving layer.
This role carries significant influence. The architectures you design become reference patterns. The feedback you bring back shapes the product roadmap. And the trust you build with customers becomes the foundation of long-term partnerships. We want someone who takes that seriously and operates with the technical depth and customer instinct to back it up.
Responsibilities
- Solution Architecture: Design end-to-end technical architectures that integrate ai&'s agent and inference platform into customer environments. Own the solution from initial scoping through deployment, ensuring it is correct, scalable, and production-ready.
- Technical Customer Engagement: Serve as the primary technical point of contact for enterprise customers. Lead deep-dive architecture sessions, proof-of-concept engagements, and technical reviews. Operate as a peer to the customer's most senior engineers.
- Platform Expertise: Develop and maintain deep expertise across the full ai& platform — inference serving, model capabilities, agentic frameworks, and infrastructure. Be the person who knows it better than anyone outside the company.
- Proof of Concept & Benchmarking: Lead technical proof-of-concept engagements with customers. Design benchmarks that demonstrate platform performance against customer workloads and use the results to guide architectural recommendations.
- Agentic Workflow Design: Help customers architect and deploy agentic workflows on ai& infrastructure. Translate complex customer use cases into concrete, well-scoped implementation plans and build alongside them where needed.
- Technical Troubleshooting & Escalation: Own technical issue resolution across the customer lifecycle. Diagnose problems at any layer of the stack, drive resolution with internal engineering teams, and communicate status clearly to the customer throughout.
- Customer Feedback & Roadmap Input: Systematically capture and communicate the technical signal you gather in the field. Be the voice of the customer inside ai& and ensure product and engineering decisions are informed by real deployment experience.
- Reference Architecture & Enablement: Produce reference architectures, integration guides, and example implementations that scale your expertise beyond the customers you directly touch.
Requirements
- Solution Architecture Experience: You have designed and delivered end-to-end technical solutions for enterprise customers in a solutions architect, field engineer, or equivalent role. You think in systems and you own the architecture through to production.
- AI Infrastructure Depth: Deep familiarity with AI inference infrastructure, serving frameworks, and the systems that surround them. You understand how models are deployed, how serving stacks are built, and where they break under real workloads.
- Agentic Systems Knowledge: You have worked with agentic frameworks and you understand the architectural patterns that make agent-based systems reliable at scale. You can design solutions that use ai&'s agentic platform to solve real customer problems.
- Enterprise Customer Fluency: You have worked with demanding enterprise customers and you know how to earn the trust of senior technical stakeholders. You communicate with precision, handle ambiguity well, and push back constructively when needed.
- Performance & Benchmarking: Experience designing and running technical benchmarks that demonstrate platform performance against real workloads. You know how to set up a POC that answers the right questions.
- Full-Stack Technical Range: Comfortable across APIs, backend infrastructure, cloud environments, and ML systems. You can diagnose problems at any layer and you do not need to hand off to understand what is happening.
- Relevant Tooling: Strong command of Python. Familiarity with inference frameworks, agentic libraries, REST APIs, and cloud deployment environments.
- Great Team Spirit: A mission-driven approach to engineering, valuing clear communication, hands-on execution, and collective success over individual silos.