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About This Role
In a world of possibilities, pursue one with endless opportunities. Imagine Next!
At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible. Job Description:
Parsons is seeking a talented Software Engineer with a passion for applying artificial intelligence and machine learning to real\-world cybersecurity challenges.
In this role, you will help integrate AI\-enabled capabilities into analyst workflows and mission systems to accelerate cyber data triage, improve decision support, and enhance operational effectiveness. This role is ideal for a technically strong engineer who understands how to stand up, assess, and guide modern AI platforms in secure government settings, with familiarity in cloud and enterprise ecosystems such as Microsoft Azure and Amazon Web Services (AWS).
What You’ll Be Doing:
- Develop full stack applications and services that leverage large language models (LLMs), retrieval\-augmented generation (RAG), agentic workflows, and other emerging AI capabilities.
- Designing, developing, and deploying AI/ML models and tools for data mining, predictive modeling, and knowledge discovery
- Integrate AI/ML\-enabled capabilities into a secure, cloud\-based data architecture, ensuring interoperability with existing systems via standardized APIs
- Implement and monitor model performance, data/concept drift, and key metrics in real time; support model retraining and fine\-tuning as new data becomes available
- Collaborate with data engineers, software developers, and stakeholders to define requirements, validate outputs, and support mission deliverables
- Ensure all AI/ML workflows comply with DoW cybersecurity, data privacy, and access control requirements, including operation within isolated cloud environments.
- Assist in knowledge transfer and training activities, including the development of tutorials and best practices for AI/ML usage.
- Educate stakeholders on AI platform concepts, emerging patterns, and implementation best practices in government environments.
- Assessing data patterns in systems and network misconfiguration.
- Working with a team of Cyber Analysts to support quick turn requests for vulnerability information by continually improving LLMs
- Conduct analyses of alternatives (AoAs) to compare internally developed approaches against commercial, open\-source, and industry\-standard techniques.
- Develop and execute experiments to assess model performance using appropriate evaluation metrics and representative datasets.
What Required Skills You'll Bring:
- Active TS/SCI with Poly
- Bachelor of Science in Computer Science, Cybersecurity, Information Systems, or related field and 10\+ years of relevant experience. With additional years of experience able to count in lieu of a degree, and vice versa.
- Familiarity with machine learning concepts, including model training, evaluation, tuning, and performance measurement.
- Ability to assess model effectiveness using quantitative metrics and communicate tradeoffs.
- Depth of experience with prompt engineering.
- Proficiency in Python and experience developing RESTful APIs and backend services.
- Experience supporting AI/ML, data, cloud, or platform engineering efforts in government, defense, or enterprise environments.
- Understanding of modern AI concepts, including LLMs, embeddings, RAG, vector search, and agentic workflows.
- Demonstrated familiarity with Microsoft and/or AWS platform ecosystems
- Proficiency using command\-line interfaces such as Windows PowerShell/Command Prompt for routine development, troubleshooting, scripting, and automation tasks
- Working knowledge of cloud architecture, containers, APIs, data services, identity/access management, and secure system integration.
- Ability to understand how AI applications depend on underlying platform components such as model hosting, pipelines, storage, orchestration, and monitoring.
- Must have demonstrated experience in database management, including designing and maintaining relational databases, writing and optimizing SQL queries, implementing backup and recovery procedures, and applying database security and performance best practices.
- Must have demonstrated experience with configuration management, including defining and maintaining configuration baselines, using configuration management tools e.g.,Ansible, Puppet, Chef, Terraform to manage infrastructure and application settings
- Passionate about AI and platform modernization.
- Ability to rapidly prototype solutions, iterate based on user feedback, and operate effectively in ambiguous problem spaces.
- Able to translate complex technical issues into actionable guidance for mixed technical and non\-technical audiences.
- Mission\-oriented, collaborative, and proactive.
Security Clearance Requirement:
An active Top Secret SCI w/Polygraph security clearance is required for this position.
This position is part of our Federal Solutions team.
The Federal Solutions segment delivers resources to our US government customers that ensure the success of missions around the globe. Our intelligent employees drive the state of the art as they provide services and solutions in the areas of defense, security, intelligence, infrastructure, and environmental. We promote a culture of excellence and close\-knit teams that take pride in delivering, protecting, and sustaining our nation's most critical assets, from Earth to cyberspace. Throughout the company, our people are anticipating what’s next to deliver the solutions our customers need now.
Salary Range: $176,900\.00 \- $332,400\.00
We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best\-in\-class benefits such as medical, dental, vision, paid time off, 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!
Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.
We truly invest and care about our employee’s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest—APPLY TODAY!
Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer to https://www.parsons.com/fraudulent\-recruitment/.
COMPETITIVE BENEFIT OFFERINGS
Financial Wellness
We care about your financial wellbeing. Parsons offers competitive pay and retirement plans to help you build wealth for the future while giving you the flexibility to diversify your investments.
Work Life Harmony
Balance in life is important and time away from the office is imperative to allow you to refresh and focus your attention on the things that matter to you. Parsons supports your time away by providing paid time off and paid flexible holidays.
Career Development
We are committed to fostering the personal and professional growth of our employees. Develop and advance yourself though our comprehensive training, educational and mentorship programs.
Veteran Support
We provide Industry leading benefits to support veterans and active\-duty members to provide security for you and your family by offering robust leave and benefits; including paid active\-duty military leave and paid time off when transitioning back to civilian life.
Mind \& Body
At Parsons we inspire healthier habits, heathier minds, and a healthier you through our wellness program. Participate in our weekly Meditation Mondays and Wellness Wednesdays. Wellness, at Parsons, is more than just your annual checkup.
Health
Health is not a one size fits all. At Parsons, we offer a robust Employee Assistance Program as well as comprehensive medical, dental and vision plans through large, national carriers with the choice of regional PPO, HDHP, or HMO networks.
Salary Context
This $176K-$332K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $190K across 251 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 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Parsons, 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 $232,000 based on 863 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($254K) sits 10% above the category median. Disclosed range: $176K to $332K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Parsons AI Hiring
Parsons has 8 open AI roles right now. They're hiring across AI Software Engineer, Data Scientist, Research Scientist, AI/ML Engineer. Positions span Annapolis Junction, MD, US, Aberdeen, MD, US, Remote, US. Compensation range: $111K - $332K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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