Our founding team includes the top minds in deep learning, model-based engineering, and industries that are our customers. We closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.).

About The Role Our Forward Deployed Engineers serve as the technical lead for each customer deployment, making key technical decisions on architecture, data integrations, and user experience for specific customer missions. On a daily basis, you will build end-to-end AI solutions, take them into production, and support our customers solving real-world physical engineering problems with novel AI capabilities.

You’ll own the technical journey from pre-sales scoping through post-deployment support and expansion, connecting Archie’s reasoning capabilities to customer data, tools, and design processes. You will also make substantial contributions to the Archie core product, with early customer adaptations and configurations reused across deployments. This is a high-impact, high-visibility opportunity with potential to scale into a leadership role.

Responsibilities

• Work with customers over the entire Archie product lifecycle: Lead discovery sessions, translate engineering challenges into AI use cases, design how Archie integrates into each workflow, and provide post-deployment support to ensure customer success.
• Designing, implement, and refine customer integrations: connect Archie to engineering data sources and tools, iterate until it delivers measurable value.
• Fine-tune and evaluate AI systems in production environments: identify, collect, and prepare customer data to fine-tune models. Source evaluation criteria and questions from customer sessions to validate improved engineering capability.
• Collaborate with engineering teams: work closely with subject matter experts and AI specialists to develop novel AI systems capable of executing critical customer engineering tasks.
• Diagnose and resolve critical issues in live deployments: drive root-cause analysis and implement durable improvements across the organization.

Who You Are You likely:

• Have shipped data-driven or AI systems to production (Python experience strongly preferred)
• Can rapidly build integrations between disparate customer systems
• Are comfortable working directly with customers and technical leaders
• Have integrated or extended AI systems. Bonus points for engineering or scientific domains!

As a Bonus, You May Have

• A physical engineering background (physics, aerospace, electrical, mechanical, etc.)
• Experience with containerized AI services in production
• Worked within compliance/regulatory frameworks for safety-critical hardware
• Delivered solutions in secure enterprise environments
• Handled live production troubleshooting and customer incident response

Our Values Mission obsession & urgency : We are obsessed with building engineering AGI as quickly as possible. We also recognize that as a startup, speed is our most precious competitive advantage. We are constantly asking ourselves what we can do to go faster. We make tradeoffs and sacrifices (personally and in the workplace) in exchange for speed.

Intellectual excellence & curiosity : We ask “what if?” and experiment liberally. We always look for better ways of doing something. We read voraciously. We challenge each other to be better. We surround ourselves with A players and we actively and unapologetically reject B players (and even B+ players⸺because they tend to surround themselves with C players).

Shipping discipline: We treat production with respect. We test and demo our product constantly. We listen attentively to our customers, users, and stakeholders, and we respect our commitments to them. We also respect our commitments to each other and will go the extra mile (or ten or one hundred) to honor them.

Ownership: We all have significant ownership stakes in the company and operate in founder mode. We believe in hierarchical requirements but not in hierarchical information flows. If we see that something is broken or can be done better, we flag it and we fix it. We encourage each other to play with and fix anything and everything... but there’s a clear owner for everything.

Interview Process

• Initial screening: Head of Talent (30 min)
• Technical manager interview: Head of Customer Engineering (45 min)
• AI system design session: customize an AI system to customer needs (60 min)
• Culture fit & mission: with co-founder & CEO (30 min)