Senior AI Systems Engineer — Client-Facing Deployments

Impruve; Chicago (IL); Hybrid; USD 150,000 - 200,000; Full time

Job summary

Impruve is a boutique forward‑deployed engineering firm that embeds with wealth management clients to deploy AI in production. As a Senior / Staff Software Engineer you’ll partner directly with clients to scope, design, and ship AI‑powered systems that solve real business problems.

This role blends hands‑on engineering across data, AI, backend and frontend, with strong emphasis on reliability, observability, and pragmatic, outcomes‑driven delivery.

Qualifications

• Strong Engineering Fundamentals: you design and ship reliable systems and turn ambiguous problems into clean production code.
• 5+ Years of Hands‑On Engineering Experience: most of it building and operating production systems.
• Cross‑Domain Fluency: you move between data, infrastructure, backend, and AI with sound call decisions.
• AI‑Native Mindset: you experiment, form opinions on what works, and bring new techniques to the team.
• Comfortable in the Room: you explain technical concepts to clients without jargon.
• Bias for Outcomes: you judge work by client impact, not output alone.

Responsibilities

• Forward‑Deployed Engineering: embed with client teams and own engagements end‑to‑end.
• AI‑Native Building: fluent with agentic development workflows and AI tooling.
• Full‑Stack Engineering: work across data, AI, backend and frontend to production.
• Systems Design: architect reliable, observable platforms with clear UX.
• Shape the Firm: help steer engagements and scale Impruve’s practice.

Skills

5+ Years Engineering

Cross‑Domain Fluency

AI‑Native Mindset

Client-facing

Bias for Outcomes

Job description

Impruve is a boutique forward‑deployed engineering firm that embeds with wealth management clients to deploy AI in production. As a Senior / Staff Software Engineer you’ll partner directly with clients to scope, design, and ship AI‑powered systems that solve real business problems.

This role blends hands‑on engineering across data, AI, backend and frontend, with strong emphasis on reliability, observability, and pragmatic, outcomes‑driven delivery.