Founding Software Engineer

Shields Group Search; San Francisco (CA); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Founding equity

Job summary

Shields Group Search is seeking a Founding Engineer for an early-stage AI startup operating across SF or NYC. You will build production-grade infrastructure and industry-specific applications, working directly with the founder and early customers on site.

This hands-on role requires owning broad parts of the stack, shaping architecture, and defining patterns for a scalable product. Equity is offered; ideal for someone who thrives in small teams and on-site collaboration in San Francisco or New

Qualifications

• 4+ years shipping production software end-to-end.
• Strong backend and systems architecture orientation.
• Experience building or standing up new systems from 0-1.
• Fundamentals in data modeling, APIs, and cloud infrastructure.
• Experience building backend-heavy or data-heavy applications.
• Hands-on with LLM-powered systems — harnesses, prompts, tools, evals.
• Comfortable building agentic systems with experimentation and reliability.

Responsibilities

• Build platform across core modules — harnesses, tools, traces, governance, cost, and integrations.
• Ship production AI applications for customers and own adoption.
• Make agents reliable with evals, traces, and guardrails.
• Integrate ERPs, CRMs, data warehouses, spreadsheets, and other systems.
• Work with customers on-site and over calls to translate needs into shipped changes.
• Build patterns into the product by reusing insights from deployments.
• Help hire and raise the level of engineering as the company grows.

Skills

Backend systems

Data modeling

APIs

Cloud infrastructure

LLM-powered systems

Agentic systems

Product mindset

Communication

Startup experience

Customer discovery

Tools

ERP integration

Job description

Founding Engineer | SF or NYC | $170K-$230K + Founding Equity

Shields Group Search is partnering with an early-stage AI startup building technology for foundational industries. The company provides enterprises with an end-to-end platform to build and scale outcomes-driven AI.

The platform is designed to help enterprises build scalable, secure, and governed AI systems at a lower total cost of ownership versus alternatives.

Its AI Command Center includes four core modules:

• Outcome OS - a system to define business outcomes and prioritize use cases
• App platform - an application delivery platform / software factory
• Control plane - a single pane of glass to govern and audit every agent
• Verticalized coding agents - agents that continuously improve applications and abstract out common patterns for reusability

About the role

As a Founding Engineer, you'll work across the entire technology lifecycle to build production-grade application infrastructure as well as deep industry-specific applications.

You'll work directly with the founder/CEO and closely with customers to crystallize their needs and transform them into product.

This is an extremely early, hands-on engineering role. The team is being built from the ground up and is expected to remain intentionally lean, with a small group of engineers working alongside the founder and a limited business/GTM team.

The work is varied: one month you might build the eval harness for a new vertical application; the next, you might stand up a customer-hosted install, integrate an ERP, or build ontologies.

The core platform combines significant traditional software engineering, backend systems, data architecture, and infrastructure work with LLM-powered and agentic systems running throughout the product.

This is not a narrowly defined frontend, ML research, or feature-development role. You should be excited to reason across different levels of abstraction, stand up entirely new systems, and work across the product stack.

What you’ll do

1. Build the platform

Contribute across all core modules - harnesses, tools, traces, governance, cost, and integrations.

You'll help architect and stand up new systems from 0-1, with a particular emphasis on backend architecture, data-heavy applications, APIs, infrastructure, and the systems connecting everything together.

2. Ship production applications

Build and deploy AI applications for customers - document understanding, deterministic pipelines, evals, and review interfaces - and own them through adoption.

3. Make agents reliable

Write the evals, traces, and guardrails that make AI output trustworthy, and use production evidence to improve it.

You should be comfortable working with agentic systems where outputs are inherently less deterministic than traditional software and where experimentation, evaluation, and iteration are essential.

4. Integrate the real world

Connect ERPs, CRMs, data warehouses, spreadsheets, and the other systems customers actually run on.

5. Work with customers

Sit with the people who use what you build, on site and on calls, and turn what you learn into shipped changes.

This requires genuine empathy for the business. You should want to understand how a CEO, CIO, CFO, or other enterprise stakeholder thinks about the business case behind an AI deployment - and ensure what you build actually delivers against that outcome.

6. Build product, not just projects

The company expects to do meaningful implementation and customer-facing work as the market develops, but the goal is to build a true product company.

You'll use what you learn from individual customer deployments to identify reusable patterns, bring those insights back into the core platform, and make the underlying product better.

7. Raise the bar

Set patterns others build on - including how the team builds with coding agents - and help hire the engineers who come next.

As the company grows, a successful Founding Engineer can have the opportunity to take responsibility for and build out an engineering group within the business.

Who you are

• 4+ years shipping production software end to end, or an exceptional record that says the same thing
• Strong backend and systems architecture orientation
• Experience building or standing up new systems from 0-1
• Solid fundamentals in data modeling, APIs, and cloud infrastructure
• Experience building backend-heavy or data-heavy applications
• Hands-on experience with LLM-powered systems - harnesses, prompts, tools, structured outputs, and evals
• Comfortable building agentic systems where experimentation, evaluation, and reliability matter
• Able to reason across multiple levels of abstraction rather than operating within one narrow piece of a system
• Product-oriented: you think beyond delivering a one-off customer solution and look for patterns that should become part of the underlying product
• Business empathy: you care about the actual business outcome the technology is supposed to produce, not simply whether the technology works
• Product taste: you notice when something is off and fix it
• High attention to detail
• Clear communicator, comfortable with customers and with ambiguity
• High agency: you find the important problem and drive it to done
• Comfortable operating on a very small, early-stage team with significant ownership and limited structure
• Ideally, you've worked in an environment where you've seen what exceptional engineering and product execution look like and can bring that standard into a company being built from the ground up
• Glad to be in person in San Francisco or New York and to spend time on site with customers as needed

This is an opportunity to join at the ground floor and help define not only the product, but how the engineering organization itself gets built.

You'll work directly with a highly technical founder, have meaningful influence over architecture and product direction, interact directly with customers, and help establish the engineering patterns future team members will build on.

For someone who performs exceptionally well, there is significant room to grow alongside the company and ultimately take ownership of an engineering group.

• Founding equity. This is a ground-floor opportunity with meaningful ownership.