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About This Role
Nightwing provides technically advanced full\-spectrum cyber, data operations, systems integration and intelligence mission support services to meet our customers’ most demanding challenges. Our capabilities include cyber space operations, cyber defense and resiliency, vulnerability research, ubiquitous technical surveillance, data intelligence, lifecycle mission enablement, and software modernization. Nightwing brings disruptive technologies, agility, and competitive offerings to customers in the intelligence community, defense, civil, and commercial markets.
Program Manager \- AI\-Enabled Software Development
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Position Overview
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Nightwing is seeking an experienced Program Manager who thrives on leading high\-performing teams, driving innovation with artificial intelligence, and strengthening our nation's security through cutting\-edge software development capabilities. Join a team at the forefront of leveraging modern AI and language models to transform how we build scalable, resilient systems that empower mission\-critical operations. Nightwing develops strategic and tactical SIGINT solutions that secure the interests of the U.S. and its partners.
Our collaborative environment embraces creativity, integrity, and constant improvement. With access to state\-of\-the\-art AI/ML tools, opportunities to grow professionally, and meaningful work alongside the nation's finest service members and engineers, you'll help shape tomorrow's development paradigm today.
This is an ONSITE position based out of our National Business Park, Maryland location.
What You Will Do:
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- Lead and mentor cross\-functional Agile development teams building next\-generation software systems that leverage AI and large language models to automate and accelerate development workflows
- Drive program execution ensuring technical performance, cost control, and schedule adherence while maintaining staffing levels across specialized disciplines including AI/ML engineers, software developers, and DevSecOps practitioners
- Champion AI/ML integration into the software development lifecycle, incorporating automated code generation, intelligent testing frameworks, and AI\-assisted development tools to increase team velocity and code quality
- Coordinate technical strategy with government stakeholders, aligning AI\-enabled delivery capabilities with evolving mission requirements and customer priorities
- Manage program metrics and performance, consistently improving award fee scores through measurable enhancements in technical innovation, contract execution, and customer engagement
- Foster innovation by identifying opportunities to apply language models and AI technologies to streamline development processes, automate repetitive tasks, and enhance developer productivity
- Ensure secure development practices, integrating AI tools within approved DevSecOps workflows while maintaining compliance with security requirements and configuration management standards
- Build and retain talent, recruiting and developing high\-performing teams with expertise in AI/ML, modern software development, and CNO capabilities
- Facilitate collaboration across product lines and mission partners to deliver integrated, performance\-driven solutions that support large\-scale operational requirements
Qualifications You Must Have:
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- Bachelor's degree in Computer Science, Information Systems, Engineering, or related STEM field
- 10\+ years of experience in software development, information security, or Computer Network Operations, with substantial technical depth
- 5\+ years of program/project management experience leading Agile software development teams delivering complex technical capabilities
- Project Management Professional (PMP) certification or equivalent
- Active TS/SCI security clearance with Polygraph
- Proven track record maintaining high staffing levels (\>90%) and driving measurable improvements in contract performance and customer satisfaction
- Technical fluency with modern software development practices, including experience with programming languages (Python, C/C\+\+, JavaScript/PHP), containerization, and CI/CD pipelines
- Strong understanding of Agile/Scrum methodologies with hands\-on experience coordinating sprint planning, backlog management, and delivery execution
- Excellent communication and leadership skills, with ability to present technical concepts to both technical teams and executive leadership
- U.S. citizenship is required
Qualifications We Prefer:
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- Master's degree in Information Assurance, Computer Science, Cybersecurity, or related field
- Direct experience implementing AI/ML technologies, large language models (LLMs), or generative AI tools into software development workflows
- Hands\-on background as a software engineer or technical lead, with experience in vulnerability research, reverse engineering, malware analysis, or CNO capability development
- Demonstrated success automating development workflows and accelerating mission readiness through technical innovation
Why Join Nightwing?
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- Lead Innovation: Spearhead the integration of AI and language models into mission\-critical development programs
- Mission\-Driven Impact: Directly contribute to programs that make the world safer and more secure
- Cutting\-Edge Technology: Work with the latest advancements in AI/ML, cloud computing, and scalable architectures
- Talented Teams: Lead brilliant engineers, data scientists, and AI specialists in a dynamic, collaborative environment that values creativity and results
- Career Growth: Expand your expertise at the intersection of program management, AI technology, and national security
- Meaningful Work: Partner with service members and government stakeholders on high\-impact CNO capabilities
Security Clearance Requirements:
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Security Clearance Type: TS/SCI with Polygraph
Security Clearance Status: Active and existing security clearance required at start
Salary \& Benefits
The salary associated with this position ($147,000\-$296,000\) is commensurate with the selected candidate’s qualifications, years of relevant experience, and demonstrated level of expertise. Compensation will be determined based on these factors to ensure alignment with skills, responsibilities, and market standards.
Nightwing offers medical, vision and dental insurance coverage in addition to a 401k plan, PTO, Holidays, and additional insurances.
*Nightwing is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.*
Salary Context
This $147K-$296K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Nightwing, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $147K to $296K.
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.
Nightwing AI Hiring
Nightwing has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Annapolis Junction, MD, US. Compensation range: $296K - $296K.
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/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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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