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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, 10% 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.*\*Please be aware that this position is contingent upon capturing program award(s) and obtaining and maintaining associated business and/or customer funding. Furthermore, this position is contingent upon the candidate obtaining final clearances and program access(es) within a reasonable period of time as determined by the company. Continued employment thereafter will be subject to maintenance at the level of clearance and program access required for the position in the future\Expand your horizons, advance your career, and contribute to a secure future for generations. Northrop Grumman’s Space Sector invites you to bring your pioneering spirit to our collaborative teams. As an *AI Software Engineer* *– Level 3* supporting our Space team, this role can be based at our Dulles, VA** location. On our team, you’ll be a linchpin in missions of paramount importance, defining the art of the possible from day one.
We are looking for early to mid\-career AI researchers and engineers with deep knowledge of Computer Science and a deep focus on Reinforcement Learning (RL) to design and implement intelligent autonomy algorithms for our space and aerospace programs.
Job Responsibilities
*In this role you will:*
- Perform Novel Algorithm R\&D
- Design and implement state\-of\-the\-art RL / SL algorithms drawn from the latest literature
- Rapidly prototype in Python/JAX/PyTorch, then port to embedded C\+\+/CUDA
- Develop Physics\-Based Autonomy to perform Mission Planning \& Decision\-Making
- Apply supervised learning, reinforcement learning, and other AI/ML techniques to high\-fidelity astrodynamics planning and controls problems, including real\-time constraint handling
- Fuse learned policies with classical GNC filters for robust guidance, navigation, and closed\-loop control
- Build models that re\-optimize delta\-V, power, and comm\- (among other) constrained timelines using neural search or differentiable optimization
- Develop AI solutions for real\-time anomaly detection and response to ensuring robust and adaptive spacecraft operations. This includes developing models that detect out\-of\-family telemetry and select corrective actions via hierarchical or policy\-gradient RL
- Lead Verification \& Flight Readiness
- Lead Monte\-Carlo, Processor\-in\-the\-Loop, Hardware\-in\-the\-Loop, and digital twin campaigns to prove safety and performance via internal standards
- Participate in the full life cycle of software development, including requirements development, modeling and design, application development, unit to CSCI testing, integration, formal system testing, release, installation, and maintenance
In this role, you will be developing systems for a variety of spacecraft using current technologies and others yet to come! We are seeking team members who have a thirst for knowledge, approach each day with optimism, and have a relentless drive to solve complex problems. Creativity and innovation are imperative for this role, because at Northrop Grumman, many of the problems we work on are impossible… until they’re not.
*To be successful in this role you should have:*
- Strong interest in space, national security, and related mission areas
- Be an active and integral member of your team
- Channel your enthusiasm to innovate
- Be part of a supportive team that develops and deploys technologies that matter to our national security
- Work with agility, flexibility, and collaboration to explore creative ideas
This position is 100% onsite and cannot accommodate telecommute work. This position will work a 9/80 schedule, with every other Friday off.
*This position is contingent upon the candidate verifying and/or obtaining final clearances and program access(es) within a reasonable period of time as determined by the company.*
Basic Qualifications: (*must have to be considered*)
- Must have the ability to obtain and maintain a U.S. Government DoD Top\-Secret (TS) security clearance and Sensitive Compartmented Information (SCI) approval/access \[TS/SCI] within a reasonable period of time.*US citizenship is required.*
- Level 3: (*Principal level*)
+ Bachelor’s degree with a minimum of 5 years of relevant AI engineering experience
- *May consider an additional 4\+ years of experience in lieu of a completed degree*
+ Master’s degree with a minimum of 3 years of relevant AI engineering experience
+ PhD with a minimum of 1 year of relevant AI engineering experience
- Industry knowledge and/or foundational education of AI, with a focus on ML, RL, or SL model development
- Experience with machine learning usage in a product line environment
- Experience with hands\-on coding of learning algorithms from primary literature—comfortable translating equations to optimized code
- Experience with physics\-based AI application (e.g. for spacecraft, robotics, autonomous aircraft, drones, rockets, or similar) in academia or industry
- Experience in developing scalable RL/SL and other ML pipelines, with a track record of designing novel algorithms tailored to complex, real\-world dynamics
- Experience/proficiency in software engineering best practices and standards
- Experience in simulation development for space vehicle applications
- Experience in Embedded Software, Space Flight Software, or Simulation Software
- Experience with Python, CUDA, C/C\+\+ programming
Preferred Qualifications:
- Current/Active TS/SCI
- MS or PhD in Computer Science or Reinforcement Learning, or STEM degree field with strong physics\-based numerical modeling and AI/ML experience
- Diverse programming proficiency: C/C\+\+, Python, MATLAB/Simulink, Windows/Linux scripting
- Demonstrated systems engineering excellence in requirements analysis, modeling and simulation, verification and validation at subsystem and system level or Demonstrated vehicle development, mission systems integration, ground and flight test validation experience
- Experience in successfully developing and integrating software and hardware solutions for space applications
- Experience in system and subsystem specification development including verification methodologies
- Experience implementing action plans based on metrics and/or root cause/corrective actions
- Hands\-on technical experience with spacecraft or satellite related systems
- Proven experience working with technically diverse teams across multiple locations
- Experience with Space Flight Software, Simulation Software
If this job description reads like it was written specifically for you, consider joining our team!
Curious about all the exciting developments with the Northrop Grumman Space Sector? Click the link below:
https://www.northropgrumman.com/space
Working at Northrop Grumman is more than just a paycheck. We offer a comprehensive Total Rewards and benefits package designed to help you thrive at work and in life. For more information on our Total Rewards package, please visit our Total Rewards site.
Northrop Grumman Total Rewards
Primary Level Salary Range: $125,300\.00 \- $206,800\.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 $125K-$206K range is below the median for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 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 $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($166K) sits 24% below the category median. Disclosed range: $125K to $206K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Northrop Grumman AI Hiring
Northrop Grumman has 5 open AI roles right now. They're hiring across Data Scientist, Research Scientist, AI Software Engineer. Positions span Remote, US, Corinne, UT, US, Dulles, VA, US. Compensation range: $147K - $206K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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