AI Engineer

Smart Bricks; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 280,000; Full time

Job summary

Smart Bricks is an AI lab building autonomous reasoning systems for live, production environments. As an AI Engineer, you’ll work across the full model and agent stack, from research and experimentation to deployment and live monitoring, ensuring models stay accurate and reliable in real-time.

You will own end-to-end pipelines, implement agentic orchestration with LangChain, and collaborate with data engineers to optimize feature stores and serving latency in a fast-paced, implications-driven

Qualifications

• Hands-on production ML experience across training, deployment, and live monitoring.
• Experience building agentic systems and orchestration using LangChain or similar frameworks.
• Hands-on with LLMs, RAG pipelines, and vector search infrastructure.
• Proficiency in Python; comfortable with PyTorch or TensorFlow in production.
• Demonstrated ability to own features end-to-end and communicate across teams.

Responsibilities

• Build, deploy, and maintain production AI models for valuation, forecasting, scoring, and classification.
• Develop LangChain-based orchestration workflows and contribute to custom agent framework
• Design and improve RAG pipelines and vector search infrastructure for domain retrieval.
• Collaborate with data engineers to improve feature store quality and serving latency.
• Build and maintain model monitoring, drift detection, and retraining triggers.
• Contribute to full MLOps lifecycle: experiment tracking, versioning, deployment, rollback.

Skills

Production ML engineering

LangChain orchestration

LLMs / RAG pipelines

Python

Clear communication

Ownership

Tools

PyTorch

TensorFlow

Docker

Kubernetes

AWS

LangChain

Snowflake

Pinecone

Kafka

Spark

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 team working on genuinely hard problems at the intersection of AI infrastructure and one of the world's largest industries. Everything we build is live in production, consequential, and compounding in capability with every data point the system generates.

About The Role

As an AI Engineer at Smart Bricks, you will work across our full model and agent stack in production. This is not a demo environment - everything we build is live, consequential, and improving with every data point the system generates. You will work on agentic orchestration, production model deployment, real-time data infrastructure, and the feedback loops that make the system smarter over time. You will own what you build end-to-end, from research and experimentation through to deployment and live monitoring.

What You Will Work On

• Building, deploying, and maintaining production AI models across valuation, forecasting, scoring, and classification tasks - validated against real-world outcomes
• Developing and optimising LangChain-based agentic orchestration workflows and contributing to our custom agent framework
• Designing and improving our RAG pipeline and vector search infrastructure for domain-specific retrieval and explainability
• Collaborating with data engineers to improve feature store quality, coverage, and serving latency
• Building and maintaining model monitoring infrastructure - drift detection, performance tracking, and automated retraining triggers
• Contributing to the full MLOps lifecycle - experiment tracking, model versioning, deployment pipelines, and rollback protocols

We Expect You To

• Have strong production ML engineering experience - model training, evaluation, deployment, and live monitoring
• Be comfortable building and maintaining agentic systems using LangChain or equivalent orchestration frameworks
• Have hands-on experience with LLMs, RAG pipelines, and vector search infrastructure
• Be proficient in Python and comfortable working across PyTorch or TensorFlow
• Have experience deploying containerised ML systems - Docker, Kubernetes, AWS
• Take full ownership of what you build and care deeply about model quality in production
• Communicate clearly across engineering and research - you work at the boundary between both

Nice To Have

• Experience with gradient boosted models (LightGBM, XGBoost) and geospatial ML
• Familiarity with Snowflake, Pinecone, Apache Kafka, or Spark
• Background in applied AI in a financial services or data-intensive production setting
• Experience with serverless inference - AWS Lambda or equivalent

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.