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About This Role
RELOCATION ASSISTANCE: Relocation assistance may be available
CLEARANCE REQUIRED FOR START: Yes
CLEARANCE TYPE: Top Secret
TRAVEL: Yes, 25% of the TimeDescription
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At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history \- from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.
Northrop Grumman Aeronautics Systems is seeking a Senior Principal Software Engineer – AI Software to join our onsite team on site in San Diego, El Segundo or Palmdale, California.
This role requires a self\-motivated professional with proven experience collaborating in cross functional teams. The ideal candidate will be a technology visionary and strategist who can lead the strategy, architecture, and hands\-on implementation of secure, reliable, and scalable Artificial Intelligence systems that drive measurable business outcomes. This position demands strong interpersonal skills, the ability to influence stakeholders, and a proven track record of delivering results in highly regulated, high clearance environments.
Roles and Responsibilities:
- Provide collaborative technical leadership that drives the maturation of Artificial Intelligence solutions across a portfolio of contracts and operating units
- Partner with product, platform, data, security, and compliance to establish responsible AI practices, model governance, and enterprise\-grade MLOps.
- Act as the Subject Matter Expert for all aspects of the enterprise Artificial Intelligence roadmap and execution.
- Provide senior technical leadership thorough design reviews, prototyping, code contributions, and mentoring while aligning roadmaps across teams.
Work Environment:
The selected candidate will work full time on site at our San Diego, El Segundo or Palmdale facility; remote, hybrid, or telework options are not available for this position. Travel of up to 25% may be required.
Basic Qualifications:
- Bachelor’s Degree in a STEM (Science, Technology, Engineering or Mathematics) discipline with 8 years of related engineering experience; OR a Master’s degree in a STEM discipline with 6 years of related engineering experience; OR a PhD in a STEM discipline with 4 years of related engineering experience.
- Professional software engineering experience building and delivering production software (e.g., Python, Java, C\+\+, or similar).
- Applied AI/ML engineering experience delivering models to production (classical ML and/or deep learning, including LLM\-enabled solutions).
- Experience integrating AI/ML capabilities into enterprise software systems (APIs/services, data pipelines, and production deployment patterns).
- Experience working in regulated environments with strong emphasis on security, data handling, and governance expectations for AI use.
- Demonstrated technical leadership (leading designs, mentoring engineers, driving cross\-team technical alignment).
- Active U.S. Government Top Secret clearance (with a background investigation within the past 5 years or enrolled into Continuous Evaluation).
- Ability to obtain and maintain initial Special Program Access (SAP/PAR). This SAP/PAR must be obtained within a reasonable amount of time as determined by the company to meet its business needs.
Preferred Qualifications:
- Current applicable Special Access Program (SAP) clearance.
- Advanced degree (MS/PhD) in Machine Learning, Computer Science, or related field.
- Experience with modern software practices: version control, code reviews, automated testing, CI/CD, and containerized deployment.
- Working knowledge of MLOps fundamentals (model evaluation, reproducibility, monitoring/observability, model lifecycle).
- Experience leading AI technical strategy/roadmaps for a program or product; influencing stakeholders across software, systems, and program leadership.
- Deep experience with LLM solutions, including retrieval\-augmented generation (RAG), evaluation/guardrails, and enterprise\-ready integration.
- Strong MLOps experience (pipelines/orchestration, experiment tracking, model registry, automated retraining, drift detection).
- Experience scaling AI systems for reliability/performance (latency/cost optimization, GPU utilization, autoscaling, canary/A/B deployments).
- Experience with secure DevSecOps practices and supply\-chain security for software and ML artifacts.
- Familiarity with enterprise AI governance and responsible\-use expectations, including alignment to company AI governance procedures.
Primary Level Salary Range: $142,200\.00 \- $213,400\.00
The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions.
Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business.
The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.
Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit http://www.northropgrumman.com/EEO. U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
Salary Context
This $142K-$213K range is below the median for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).
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 Northrop Grumman, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($177K) sits 19% below the category median. Disclosed range: $142K to $213K.
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.
Northrop Grumman AI Hiring
Northrop Grumman has 14 open AI roles right now. They're hiring across AI Software Engineer, Data Scientist, Research Scientist. Positions span Beavercreek, OH, US, Wright-Patterson AFB, OH, US, Corinne, UT, US. Compensation range: $151K - $265K.
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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