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About This Role
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the TimeDescription
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. The Northrop Grumman Space Systems, Multi-Domain Operations, and Missile Defense Integration Business Unit (BU); Advanced Programs group has an exciting career opportunity for a Staff AI/ML Software Engineer - Level 5. Join our high performing software team as the AI/ML Software Lead and come make history with us! The position is located on-site in Boulder, CO. Boulder is nestled in the foothills of the Rocky Mountains, and only 25 miles from downtown Denver.
Position Overview:
The AI/ML team lead will collaborate with team leads, systems engineers, domain experts, and software developers to identify appropriate problem formulations and opportunities for the application of AI/ML techniques. Responsibilities include developing and curating training and evaluation datasets from diverse sources, defining data management and labeling strategies, and designing scalable training, testing, and validation infrastructure consistent with program constraints and security requirements. In addition, strong leadership and organizational skills are required in order to set the AI/ML execution vision and break down tasking for the small team (<5 individuals) reporting to this leader.
Essential Functions:
- Developing and executing the overall AI/ML strategy for the team
- Drive increase in TRL level of the AI/ML solution and integration of it into the other parts of the software system while keeping in mind the limitations and challenges that come along with deploying an AI/ML application to the Edge.
- Create and maintain a roadmap for AI/ML development, ensuring continuous improvement and innovation.
- Lead the full lifecycle of AI/ML project implementation, from problem definition and data collection to model development, deployment, and monitoring.
- Oversee the design, development, and implementation of AI/ML models and algorithms using appropriate tools and techniques.
- Monitor the performance of AI/ML models in production and identify areas for improvement.
- Explore and evaluate new AI/ML techniques and tools.
- Work with stakeholders to define problem statements and success metrics for AI/ML initiatives.
- Collaborate with Program Management, Chief Architect, Systems Engineer, Technical Team Leads to ensure AI/ML roadmap matches the SOW objectives for the contract and integrates into the existing software system as needed
- Confidently present AI/ML roadmaps, progress, analysis and other related results at customer events and demonstrations
- Prepare and present AI/ML findings and recommendations to senior management and stakeholders.
- Communicate AI/ML concepts and results effectively to both technical and non-technical audiences.
- Be cognizant of deadlines and timelines
- Build strong relationships with internal and external partners.
Basic Qualifications:
- Staff AI/ML Software Engineer – Level 5 : Bachelor’s Degree in a STEM (Science, Technology, Engineering or Mathematics) discipline from an accredited university and 12 years of related experience, or a Master's Degree in STEM and 10 years of related experience, or 8 years of experience with a PhD in STEM.
- Applicants must have an active in-scope U.S. Government DoD Secret security clearance is required to start; with the ability to obtain and maintain a Top Secret/SCI (TS/SCI) security clearance.
- Recent C++ experience
Preferred Skills:
- Experience leading technical teams
- Knowledge python, and DevSecOps development environments
- Experience with Agile program execution (Tools for Agile, JIRA, Confluence)
- Experience with microservice based scaling architectures (Kubernetes, Docker, Podman)
- Experience developing and deploying machine learning models on edge platforms, using frameworks such as LiteRT (formerly TensorFlow Lite).
- Experience with feature selection and model design for ML algorithms applied to tracking applications.
- Familiarity with distributed systems concepts, including resource allocation and coordination across multiple nodes.
- Experience applying data management techniques (e.g., data organization, storage, retrieval, and quality control) in support of ML/analytics workflows.
- Expertise in a wide range of AI/ML techniques, including deep learning, natural language processing, computer vision, and reinforcement learning.
- Experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and Keras.
- Expertise with Large Language Models/Generative AI and Prompt Engineering. Also, using LLM/GAI solutions for usage in human-machine teaming for Software Development.
- Proficiency in data mining, data analysis, and data visualization.
- Experience with cloud computing platforms such as AWS, Azure, or GCP.
- Experience with big data technologies such as Hadoop, Spark, and Hive.
- Familiarity with DevOps practices and tools.
- Excellent leadership and management skills.
Primary Level Salary Range: $214,200.00 - $321,200.00 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 $214K-$321K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $193K across 172 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 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% 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 $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($267K) sits 22% above the category median. Disclosed range: $214K to $321K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Northrop Grumman AI Hiring
Northrop Grumman has 14 open AI roles right now. They're hiring across Research Scientist, AI Software Engineer, AI/ML Engineer, Data Scientist. Positions span WV, US, Chandler, AZ, US, Remote, US. Compensation range: $123K - $321K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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