Forward Deployed AI Engineer

Role Overview
As a Forward Deployed AI Engineer (FDE) in our Chicago hub, you will operate at the front lines of the AI revolution, acting as an elite technical bridge between our core research breakthroughs and our most strategic customers. Unlike traditional software engineers, you are embedded directly within client environments to solve their hardest, highest-stakes problems by building and shipping production-grade Generative AI systems. You operate with the autonomy of a founder and the technical rigor of a staff engineer to turn messy, real-world data into measurable business value.
You will own the entire lifecycle of AI deployment—from initial discovery and scoping to the development of full-stack systems and guiding the path to client integration. Your success is measured not just by the code you write, but by the client adoption and the workflow impact realized by the client.

Key Responsibilities:
AI Deployment & Production Engineering
Own technical delivery for complex end-to-end deployments of frontier models, from the first prototype to stable, scalable production systems.
Design and build production-grade Retrieval-Augmented Generation (RAG) systems, agentic workflows, and custom data pipelines over proprietary enterprise data.
Optimize AI workflows for performance, low latency, and reliability under real-client constraints.
Harden systems for security and compliance, ensuring models operate safely within regulated environments.
Utilize advanced AI coding assistants or agentic development tools such as Claude Code, OpenAI Codex, Google Antigravity, GitHub Copilot, or AWS Kiro regularly to meet client needs

Embedded Problem-Solving & Feedback
Embed deeply with customer engineering teams to map vague business challenges (e.g., "reduce fraud") into concrete technical plans.
Act as the primary technical owner, troubleshooting complex production outages and serving as the last line of defense in the field.
Share critical field feedback and eval-driven data with core Product and Research teams to influence the model roadmap and platform GA features.
Codify successful field patterns into reusable tools, playbooks, or infrastructure building blocks for the broader organization.

Client Advisory & Transformation
Advise senior client stakeholders (C-suite, business, and technical leaders) on how to leverage AI and data for strategic advantage.
Guide clients through the end-to-end journey—from ideation and business case development to implementation and change management.
Ensure all solutions are responsible, ethical, and aligned with evolving industry regulations.

Relevant Industry Experience
P&C (Property and Casualty) Insurance Expertise (Underwriting, Operations, Call Center, Claims)
Understanding of business (BFSI) that require intensive governance, compliance and security when it comes to AI execution and implementation

Who You Are
A hands-on builder with a "radical ownership" mindset—you don't file tickets, you fix problems across the full stack.
Comfortable with C-level dialogue and capable of translating complex AI systems into business language for non-technical executives.
Highly proficient in Python, SQL, and building applications with AI APIs (OpenAI, Anthropic, etc.).
Experienced in cloud infrastructure and containerization (Docker, Kubernetes) to deploy solutions directly in customer clouds.
Proven ability to integrate technology solutions within regulated financial services environments, with a focus on compliance and risk management specific to the insurance industry.

Optional / Preferred Skills
Hands-on experience with Google Vertex AI for model development, orchestration, and tuning.
Experience implementing Gemini-powered applications and leveraging Gemini Code Assist.
Familiarity with Google Cloud Platform services like BigQuery, Dataflow, and GKE for AI infrastructure.
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