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About This Role
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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:
Job Description:
Parsons is looking for a highly skilled ML/AI Engineer to join our Joint Staff Chief Digital and Artificial Intelligence Office (CDAO) team. In this role, you will design, develop, and operationalize AI/ML capabilities within Maven Smart System (MSS) Foundry, enabling automated processing and intelligent management of lessons-learned data. You will develop agentic AI workflows, production-grade APIs and services, and MLOps capabilities that enable AI models to be deployed, monitored, validated, and continuously improved within secure DoD environments.
What You'll Be Doing:
- Design and implement AI agentic workflows that automate classification, summarization, enrichment, and intelligent routing of lessons-learned information
- Develop and integrate AI/ML capabilities within MSS Foundry applications and supporting mission systems
- Design, develop, and maintain robust APIs and services that enable AI capabilities to interact with Foundry applications, data platforms, and external systems
- Leverage Databricks MLOps capabilities, including MLflow and Databricks Workflows, to support model lifecycle management, orchestration, experimentation, and deployment
- Develop automated processes for model validation, evaluation, monitoring, and continuous improvement of AI/ML capabilities
- Design scalable AI/ML solutions capable of operating reliably in production environments
- Integrate structured and unstructured data sources to support AI-enabled mission workflows
- Collaborate with software engineers, data engineers, mission stakeholders, and other technical teams to translate operational requirements into AI/ML solutions
- Monitor production AI/ML systems and troubleshoot performance, reliability, and integration issues
- Apply responsible AI, security, data governance, and model management practices appropriate for secure DoD environments
What Required Skills You'll Bring:
- Active TS/SCI security clearance
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field
- Minimum 5 years of experience in machine learning, AI engineering, software engineering, or a related technical field
- Hands-on experience developing and deploying machine learning or AI solutions in production environments
- Experience developing AI/ML APIs, services, or application integrations
- Proficiency in Python and experience with modern AI/ML frameworks and libraries
- Experience with MLOps and machine learning lifecycle management
- Experience with Databricks, including MLflow and/or Databricks Workflows
- Experience developing, orchestrating, and monitoring production AI/ML workflows
- Strong understanding of model evaluation, validation, monitoring, and performance optimization
- 7 years of related work experience
What Desired Skills You'll Bring:
- Experience with Palantir Foundry / MSS Foundry
- Experience developing AI agents, agentic workflows, or LLM-powered applications
- Experience with LLMs, prompt engineering, retrieval-augmented generation (RAG), embeddings, vector databases, or similar generative AI technologies
- Experience applying AI/ML to classification, summarization, information extraction, recommendation, or intelligent routing
- Experience integrating AI/ML capabilities into Foundry applications
- Experience with Databricks Model Serving, Feature Engineering, MLflow, or Unity Catalog
- Experience with REST APIs, microservices, and cloud-native application architectures
- Experience supporting Joint Staff or DoD operational missions
- Familiarity with DoD AI/ML governance, responsible AI, data security, and compliance requirements
- Experience working with structured and unstructured operational data
- Advanced degree or certifications in AI/ML, data science, cloud, or related technical disciplines
Security Clearance Requirement:
An active Top Secret SCI 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: $112,200.00 - $196,400.00 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.
Want to learn more about the benefits eligible for the Parsons’ location you are interested in?
Salary Context
This $112K-$196K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 146 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 8,943 AI roles we're tracking, AI Software Engineer positions make up 4% 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 $220,000 based on 1,448 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($154K) sits 30% below the category median. Disclosed range: $112K to $196K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
Parsons AI Hiring
Parsons has 7 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Scientist. Positions span FL, US, VA, US, MD, US. Compensation range: $130K - $266K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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