Senior Software Engineer – AI-Native Infrastructure & Systems (Remote)

Senior Software Engineer – AI-Native Infrastructure & Systems (Remote)

Compensation & Benefits:

Base salary $185,000 – $225,000+ (flexible for exceptional candidates)
Comprehensive medical through Aetna (PPO and HSA options with strong employer contribution), dental (Guardian), vision (VSP), 401(k) with match, employer-paid life insurance, and additional voluntary benefits.

About the Role:

This is not a traditional senior engineering role.
The team is building enterprise-scale data infrastructure while redefining how engineering teams operate in an AI-native environment.
AI is not a “nice-to-have” here—it is core to how work gets done. The expectation is that you already operate in a workflow where not using AI feels like coding without a computer.
You will help scale a production-grade ELT and integration platform while also designing internal AI-driven systems that significantly increase engineering velocity.
If your AI experience is still experimental or occasional, this is not the right role.

Responsibilities:

Architect and scale distributed, production-grade data systems.
Own and evolve AWS infrastructure across compute, networking, and data layers.
Build in Python and TypeScript/Node.
Design and implement AI-powered developer workflows.
Integrate AI into CI/CD, testing, and code generation.
Help define AI-first engineering standards.
Contribute to an environment where engineers and AI agents operate in parallel to deliver output.

Requirements:

7+ years of hands-on engineering experience building and operating real production systems.
Strong background in distributed systems and infrastructure.
Deep AWS experience (multi-service, hands-on); exposure to Azure & GCP a plus.
Proficiency in Python and/or TypeScript.
Experience working in small, high-output teams with a high ownership mindset.
Ability to operate across infrastructure and application layers (not purely DevOps or siloed feature work).

AI Experience (Critical):

You actively use tools such as Cursor, Claude Code, or similar in your daily workflow and rely on them to ship code faster and more effectively.
You have strong, opinionated perspectives on how AI should be integrated across an engineering team.
You can clearly articulate how you have implemented AI workflows in practice, not just experimented with them.
You are comfortable operating in an environment where some engineering tasks are intentionally designed to require heavy AI leverage to complete within time constraints.

Who This Is Not For:

Candidates whose experience is primarily DevOps/SRE without broader engineering ownership.
Those with only surface-level or occasional AI usage, individuals coming from highly abstracted or non-hands-on roles (e.g., pure Solutions Architect), or those who prefer structured, slow-moving environments over fast-paced, ambiguous build environments.

Why Join:

Direct ownership over both system architecture and engineering velocity.
Opportunity to define what AI-first development looks like in a real production environment.
Work on a live, revenue-generating platform scaling to large enterprise customers.
Small, high-caliber team where output and quality both matter.

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David Kerr

Partner

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