Software Engineer, AI Platform

District Partners; Palo Alto (CA); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Housing support

Relocation assistance

Comprehensive health benefits

Unlimited PTO

Job summary

District Partners in Palo Alto is building an early-stage AI and cybersecurity platform with a hands-on software role bridging full-stack development, applied AI, and security. You will work on Python on the backend, React on the frontend, and TypeScript across the stack while integrating AI/LLM capabilities into production software.

A fast-paced startup environment offers significant autonomy, the opportunity to influence architecture, and meaningful equity as the product scales in the Bay Area.

Qualifications

• 4–15 years of professional software engineering experience.
• Demonstrated 0-to-1 experience taking a product, platform, or major technical capability from an idea through production.
• Strong hands-on development experience across backend, frontend, or full-stack engineering, with Python, React, and TypeScript particularly relevant to the current environment.
• Experience building sophisticated production software, including SaaS platforms, enterprise applications, distributed systems, developer platforms, or similarly complex products.
• Experience in a startup, early-stage, growth-stage, or other high-ownership engineering environment.
• Exposure to AI/ML, LLMs, intelligent agents, or AI-enabled application development is highly valuable, particularly where those capabilities have made it into production.
• Cybersecurity, offensive security, red-team tooling, security automation, or adjacent experience is valuable but not required.
• Excellent computer science fundamentals with the ability to reason through architecture, systems design, algorithms, data structures, performance, and engineering tradeoffs.
• Strong academic foundation in computer science, computer engineering, or a closely related technical discipline. Candidates from rigorous engineering and computer science programs are particularly relevant.
• Strong communication skills. You can explain technical decisions, defend your thinking, absorb feedback, and collaborate with other highly technical people.
• A builder mentality. You are intellectually curious, technically ambitious, comfortable with ambiguity, and energized by problems where the answer has not already been written down.

Responsibilities

• Design and build net-new product capabilities from 0-to-1, including architecture, application logic, APIs, data flows, and production implementation.
• Build backend services primarily in Python and modern frontend experiences using React and TypeScript, moving across the stack when the problem requires it.
• Build AI and LLM capabilities into production software, moving beyond experimentation into reliable, scalable product functionality.
• Develop software supporting sophisticated security and adversarial-testing workflows, including capabilities that help identify weaknesses and evaluate how systems respond to potential threats.
• Help translate traditionally manual and expertise-heavy security workflows into scalable software and increasingly autonomous product capabilities.
• Make foundational architecture decisions around scalability, reliability, performance, and how emerging AI capabilities interact with the broader platform.
• Rapidly prototype new ideas, determine what works, and turn successful concepts into production-grade software.
• Own the full engineering lifecycle from technical design and implementation through testing, deployment, iteration, and production.
• Solve technical problems where the requirements, architecture, and implementation approach may not already exist.
• Help establish the engineering standards and technical foundation that future engineers will inherit as the company scales.

Skills

Python

React

TypeScript

Full-stack development

Distributed systems

CS fundamentals

Communication skills

Startup experience

AI/ML exposure

Education

Bachelor's degree in Computer Science or related

Job description

District Partners is supporting one of the more ambitious early-stage AI and cybersecurity companies being built right now. The company is exceptionally well capitalized, led by proven technology operators, and assembling a high-caliber engineering team to rethink how organizations identify and prepare for sophisticated cyber threats.

At the center of the platform is a technically difficult problem: using AI to emulate adversarial behavior, explore potential attack paths, test defenses, and surface security weaknesses before they can be exploited in the real world. Think next-generation red teaming built as software, with AI enabling increasingly autonomous and adaptive capabilities.

This is not another company adding an AI feature to an existing security product. AI is fundamental to what is being built, and the engineering challenge requires combining sophisticated software development with emerging AI capabilities to solve problems traditionally dependent on highly specialized human expertise.

More importantly, this is still early.

Core products are being created. Architecture is still being defined. Engineering patterns are still being established. Some of the hardest technical decisions have yet to be made.

For an engineer who wants to build, this is the window where joining actually matters. You are early enough to have real influence over the product and technical foundation, but joining a company with the capital, leadership, and ambition to build something at significant scale.

The Basics:

This is a hands-on software engineering role sitting at the intersection of full-stack product development, applied AI, and cybersecurity.

The current environment includes Python on the backend, React on the frontend, TypeScript across the application layer, and AI/LLM technologies powering increasingly sophisticated product capabilities.

The engineering problems go well beyond building another enterprise application. The team is developing software capable of modeling complex environments, exploring potential vulnerabilities, automating elements of adversarial testing, and turning large amounts of technical information into actionable security intelligence.

Cybersecurity experience is valuable, but it is not the defining requirement. The team is primarily looking for exceptional software engineers with strong computer science fundamentals who can take difficult, ambiguous problems, determine what should be built, make architectural decisions, write the code, and get it into production.

What You'll Be Owning:

• Design and build net-new product capabilities from 0-to-1, including architecture, application logic, APIs, data flows, and production implementation.
• Build backend services primarily in Python and modern frontend experiences using React and TypeScript, moving across the stack when the problem requires it.
• Build AI and LLM capabilities into production software, moving beyond experimentation into reliable, scalable product functionality.
• Develop software supporting sophisticated security and adversarial-testing workflows, including capabilities that help identify weaknesses and evaluate how systems respond to potential threats.
• Help translate traditionally manual and expertise-heavy security workflows into scalable software and increasingly autonomous product capabilities.
• Make foundational architecture decisions around scalability, reliability, performance, and how emerging AI capabilities interact with the broader platform.
• Rapidly prototype new ideas, determine what works, and turn successful concepts into production-grade software.
• Own the full engineering lifecycle from technical design and implementation through testing, deployment, iteration, and production.
• Solve technical problems where the requirements, architecture, and implementation approach may not already exist.
• Help establish the engineering standards and technical foundation that future engineers will inherit as the company scales.

The Environment:

This is genuine greenfield engineering.

There is no mature platform to inherit, no years-old architecture dictating every decision, and very little distance between an engineer and the problem being solved. The people joining now will help determine what the product and engineering organization ultimately become.

It is also unmistakably a startup.

The pace is high. Expectations are high. Engineers have significant autonomy and are expected to move with urgency, communicate clearly, challenge assumptions, and take ownership well beyond writing their portion of the code.

If you want a narrowly defined role inside a large engineering machine, this probably is not it.

If you want to sit alongside strong engineers, attack difficult technical problems, build things that did not exist before, and apply AI to a cybersecurity problem where the opposing side is constantly changing, it is a very different opportunity.

What You Bring To The Table:

• Approximately 4–15 years of professional software engineering experience. Technical depth, trajectory, and what you have actually built matter more than years alone.
• Demonstrated 0-to-1 experience taking a product, platform, or major technical capability from an idea through production.
• Strong hands-on development experience across backend, frontend, or full-stack engineering, with Python, React, and TypeScript particularly relevant to the current environment.
• Experience building sophisticated production software, including SaaS platforms, enterprise applications, distributed systems, developer platforms, or similarly complex products.
• Experience in a startup, early-stage, growth-stage, or other high-ownership engineering environment.
• Exposure to AI/ML, LLMs, intelligent agents, or AI-enabled application development is highly valuable, particularly where those capabilities have made it into production.
• Cybersecurity, offensive security, red-team tooling, security automation, or adjacent experience is valuable but not required.
• Excellent computer science fundamentals with the ability to reason through architecture, systems design, algorithms, data structures, performance, and engineering tradeoffs.
• Strong academic foundation in computer science, computer engineering, or a closely related technical discipline. Candidates from rigorous engineering and computer science programs are particularly relevant.
• Strong communication skills. You can explain technical decisions, defend your thinking, absorb feedback, and collaborate with other highly technical people.
• A builder mentality. You are intellectually curious, technically ambitious, comfortable with ambiguity, and energized by problems where the answer has not already been written down.

A Few Things Worth Knowing:

• Compensation: A high $200K base with flexibility for the right candidate, plus meaningful early-stage equity.
• Equity: Meaningful ownership at an early stage.
• Housing Support: Additional housing assistance is available for employees who live close to the office.
• Relocation: Relocation support is available for candidates moving to the Bay Area.
• Benefits: Comprehensive health benefits and unlimited PTO.