Forward Deployment Engineer

Smart Bricks; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Smart Bricks, a frontier AI lab, seeks a Forward Deployment Engineer to own the technical integration of our AI infrastructure into client workflows. You will write production code, build integrations, and operate agentic workflows at the edge of capabilities, shaping the product through direct feedback to engineering.

You will deploy AI/ML systems in real-world environments, design scalable data pipelines, and collaborate with a small, high-conviction team building live-in-production

Qualifications

• Must have strong software engineering foundation with production code experience.
• Experience deploying AI/ML systems in real environments.
• Ability to translate complex technical concepts for stakeholders.

Responsibilities

• Design and build production-grade integrations between our API layer and external systems.
• Deploy and configure AI agent workflows for operational contexts.
• Write production code, build data pipelines, and debug distributed systems in client environments.
• Collaborate with engineering to feed deployment learnings back into product.

Skills

Software engineering

API integrations

Data pipelines

Cloud infrastructure

AI/ML deployment

Problem-solving

Tools

GraphQL APIs

Apache Kafka

Snowflake

Kubernetes

Job description

Smart Bricks is a frontier AI lab building autonomous reasoning systems that allow capital to discover, evaluate, and transact assets end-to-end. We are a small, high-conviction team working at the frontier of applied AI - and we are expanding how our infrastructure integrates with the sophisticated organisations that depend on it. Everything we build is live in production, operating at scale, and compounding in capability over time.

About The Role

As a Forward Deployment Engineer at Smart Bricks, you will own the technical integration of our AI infrastructure into the workflows of sophisticated external organisations. This is a deeply technical role that sits at the most commercially critical point in the business - where our AI capability meets the real world. You will write production code, build integrations, configure agentic workflows for specific operational contexts, and operate at the edge of what our system can do. You will also feed what you discover back into engineering, directly shaping how the product evolves.

What You Will Work On

Designing and building production-grade integrations between our API layer and external systems - data warehouses, portfolio management platforms, CRMs, and custom internal tools

Deploying and configuring AI agent workflows for specific operational contexts - translating general-purpose agent capability into precise, auditable, production-ready implementations

Writing production code, building data pipelines, and debugging complex distributed systems in real-world client environments

Collaborating closely with our core engineering team - translating what you observe in deployment back into product and infrastructure improvements

Operating at the technical frontier of what our stack can do - finding the edges of the system, stress-testing assumptions, and expanding what is possible

Engaging directly with technical counterparts at sophisticated organisations - translating between their infrastructure and ours at depth, without losing technical fidelity in either direction

We Expect You To

Have a strong software engineering foundation - production code, API integrations, data pipelines, and cloud infrastructure

Have experience deploying AI or ML systems in real-world environments - not just building them in controlled settings

Be comfortable moving between deep technical implementation and high-stakes technical conversations without losing fidelity in either direction

Demonstrate strong problem-solving instincts in ambiguous, fast-moving situations

Take ownership of outcomes, not just tasks - you are accountable for integrations working reliably in production

Communicate technical complexity clearly to both engineering peers and non-technical stakeholders

Nice To Have

Experience in solutions engineering, technical implementation, or forward deployment at a high-growth AI or infrastructure company

Familiarity with agentic AI systems, LLM tooling, or RAG pipelines

Experience with GraphQL APIs, Apache Kafka, Snowflake, or Kubernetes

Background in financial services, enterprise software integration, or data-intensive production environments

Why Smart Bricks

Solve Hard Problems: Work on AI systems that are live in production - agentic orchestration, real-time inference, cross-market model transfer, and retrieval systems operating at scale on proprietary data that doesn't exist anywhere else.

Build What's Next: The infrastructure we are building sits at the frontier of applied AI. The models, agents, and reasoning systems you work on here will define how one of the world's largest asset classes operates for decades.

Ownership and Impact: Small team, no bureaucracy, high trust. Your work ships, your decisions matter, and your fingerprints are on everything we build.

Learn from the Best: Collaborate with world-class engineers, researchers, and operators who left careers at leading AI labs and financial institutions to build something genuinely new.