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About This Role
The Nuclear Company is the fastest growing AI tech\-startup in the nuclear and energy space, pioneering a fleet\-scale approach to building the next generation of nuclear reactors. Through our design\-once, build\-many model, we're accelerating the deployment of safe, reliable, and affordable nuclear energy.
We operate with an AI\-first mindset. Every employee is expected to leverage AI, technology, and the Nuclear Operating System (NOS) as integral components of their role to improve the quality, speed, and impact of their work. We expect every team member to continuously identify opportunities to automate workflows, enhance decision\-making, improve processes, and contribute to the ongoing evolution of NOS as a strategic operating capability that enables The Nuclear Company to scale with excellence.
We hire people who are driven by purpose, thrive in ambiguity, and are energized by building what has never been built before. Our team combines intellectual curiosity with high agency, embraces candid feedback and continuous learning, and holds themselves and others to exceptional standards. Our values—Trust, Responsibility, Unity, Scrappiness, and Tenacity—guide how we hire, collaborate, and make decisions every day. They are not words on a wall; they are the standard by which we operate. Trust is the foundation of our safety culture, fostering intellectual honesty, accountability, and open communication, while our values challenge every team member to execute with urgency, humility, resilience, and an unwavering commitment to our mission.
About the role
The United States is building nuclear power again, and The Nuclear Company is writing the software that makes it possible. NOS, the Nuclear Operating System, runs the regulatory, supply chain, cost, schedule, and field work behind real reactor construction. The work matters for national security, energy independence, and the climate.
You will build software that people use to build power plants. As a AI Software Engineering Intern, you take real scope on NOS across one of our engineering squads (product, platform, or data), and increasingly that means AI\-powered software: LLM\- and agent\-backed features, retrieval, and tool\-calling in the tools our teams use. You work next to full\-time engineers and nuclear experts, ship real features to production, and see your work put to use by the teams building plants.
This is a six\-month co\-op available in the Fall 2026 (August to December) cycle, aligned to the academic calendar. Base location is Washington DC, on\-site five days a week, with full housing and relocation for co\-ops outside the DC metro area.
Responsibilities
- Build new features and full modules within NOS: regulatory automation, cost and schedule, supply chain, and the commercial portal.
- Build AI\-powered software: LLM\- and agent\-backed features, retrieval\-augmented generation, and tool\-calling against internal systems, a growing part of the platform.
- Develop data integrations across Palantir Foundry, AWS GovCloud, and more.
- Convert build\-a\-thon prototypes into production\-grade features and build field deployment tooling for the teams working in the field.
- Build the automated testing and compliance infrastructure that keeps NOS audit\-ready; triage issues and root\-cause failures
Required Experience
- Currently enrolled in a BS in Computer Science, Software Engineering, Computer Engineering, Mathematics, Physics, or a related technical field. Available for a full six\-month term and returning to school afterward.
- Strong programming fundamentals in at least one modern language (Python, TypeScript, Java, Go, Rust, or C\+\+).
- A track record of shipping working software (course projects, personal projects, or prior internships or co\-ops).
- This position requires access to information and technology subject to U.S. export controls (including DOE 10 CFR Part 810 and NRC requirements). U.S. Person status (U.S. citizen or lawful permanent resident) is required, and TNC does not provide visa sponsorship for these roles.
- Willing and able to work on\-site in Washington DC, five days a week, for the full six\-month term.
Preferred Experience
- Exposure to building AI\-powered features: LLM APIs (OpenAI or Anthropic), retrieval\-augmented generation, or agent and tool\-calling.
- Coursework or project experience with Palantir Foundry, AWS, or another enterprise cloud platform.
- Familiarity with algorithms, data structures, cloud infrastructure, and modern front\-end frameworks.
- Interest in energy, national security, industrial software, or regulated industries.
- Familiarity with nuclear engineering concepts (not required, we teach the domain).
Benefits
- Competitive compensation packages
- 401k with company match
- Medical, dental, vision plans
- Generous vacation policy, plus holidays
Estimated Starting Salary Range
The estimated starting rate for this role is $25\.00 an hour plus a $2,000 monthly housing stipend less applicable withholdings and deductions, paid on a bi\-weekly basis. The actual pay offered may vary based on relevant factors as determined in the Company's discretion, which may include experience, qualifications, tenure, skill set, availability of qualified candidates, geographic location, certifications held, and other criteria deemed pertinent to the particular role.
EEO Statement
The Nuclear Company is an equal opportunity employer committed to fostering an environment of inclusion in the workplace. We provide equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We prohibit discrimination in all aspects of employment, including hiring, promotion, demotion, transfer, compensation, and termination.
Export Control
Certain positions at The Nuclear Company may involve access to information and technology subject to export controls under U.S. law. Compliance with these export controls may result in The Nuclear Company limiting its consideration of certain applicants.
Recruiting Fraud Alert
Your safety is our priority. We want to ensure your job search stays secure. Please note that the team at The Nuclear Company only communicates through official @thenuclearcompany.com email addresses. We will never ask for payments or sensitive financial information at any stage of our recruitment process. For your peace of mind, please verify all openings and submit your applications directly through our official careers page.
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Nuclear, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,000.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Nuclear AI Hiring
Nuclear has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Washington, DC, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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