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About This Role
Active Top Secret (TS/SCI) clearance with polygraph is required.
Visionist has an exciting new, fully FUNDED opportunity for a Senior Applied AI Engineer \- Software Engineering on our largest PRIME contract. Our team of Analysts and Engineers is motivated by the direct impact on the mission, crafting specialized tools for enhanced efficiency and quick iterations for our operations user base. Seeing your tools in real\-time action brings immediate gratification. This premier program encompasses traditional software services including Systems Design and Engineering, Database Administration, Data Science and Knowledge Management, Enterprise Risk Management, Integration and Test, as well as Operations and Systems Support. The program is characterized by innovation and excitement, fostering meaningful engagements, and offering distinctive collaboration opportunities with users, policy makers, and mission leadership, all while maintaining a service mindset. If you thrive in a collaborative work environment and enjoy utilizing a diverse tech stack, then this opportunity is tailor\-made for you!
For over 15 years, Visionist has been solving the Intelligence Community's toughest software and analysis challenges. As a 100% employee\-owned company, we prioritize our people—your job security is assured. We embed small engineering teams with analysts to rapidly identify and solve mission capability gaps playing a critical role in defending our nation’s cyber infrastructure \& providing expertise in malware analysis, attribution, mapping adversarial infrastructure, pen testing, and operational planning. Our open\-door leadership team fosters a supportive culture, where internal growth and promotion opportunities are the norm. Don’t just take our word for it—check out our 4\.8\-star review on Glassdoor. Join a company that feels like a family with regular happy hours, baseball games, activity clubs and more. Check us out at www.visionistinc.com.
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Your contributions are…
- Design, develop, and maintain production AI\-enabled software applications using Python and modern software engineering practices
- Architect and implement LLM\-powered workflows, retrieval\-augmented generation (RAG) pipelines, and AI agent capabilities that solve mission problems
- Develop backend services, APIs, and data pipelines supporting AI\-enabled applications
- Translate natural language user requests into deterministic analytical workflows through integration with mission data sources, databases, and search platforms
- Collaborate directly with mission stakeholders to understand operational workflows and rapidly prototype customer\-focused AI solutions
- Integrate structured and unstructured data from multiple sources into scalable AI applications
- Evaluate emerging AI frameworks, models, and software engineering techniques for mission applicability
- Mentor junior engineers and contribute to technical architecture, engineering standards, and software design across the team
Requirements for your new career…
- Bachelor's degree in a technical discipline. (Additional 4 years of experience may substitute degree)
- 12 years of experience in software development
- Production software development experience using Python
- Experience designing and developing distributed or backend software systems
- Experience building AI\-enabled applications using LLMs, retrieval\-augmented generation (RAG), AI agents, or similar technologies
- Experience developing REST APIs and integrating multiple data sources
- Experience working with SQL, Elasticsearch, or other data storage technologies
- Strong understanding of software architecture, object\-oriented design, and software engineering best practices
- Strong analytical and problem\-solving skills
- Experience collaborating directly with mission customers to understand requirements and deliver operational solutions
- Ability to communicate technical concepts to both technical and non\-technical stakeholders
Benefits of becoming a Visionist: Your New Career
- We are a 100% employee\-owned company, so our employees see the benefit of their contributions and have a stake in our overall success!
- Competitive 15% retirement contribution! (5% 401K match \& 10% ESOP)
- 4 weeks paid time off that is never “use or lose”, 12 paid holidays, comp time, overtime, AND flexible work hours
- 80 hours of paid parental leave with an additional $8,000 supplemental payment upon returning from maternity
- Medical, dental, \& vision benefits for both individuals and families (those who waive medical benefits will receive an additional $4,160/year)
- Annual lifestyle bonus of $600 – use it towards gyms/fitness, new tech, or your HSA!
- Annual merit increases \& performance\-based bonuses
- Term life insurance, short\-term disability, \& long\-term disability
Salary range: $170,000 \- $240,000
Disclaimer: Salary for this position, along with additional compensation options, will be determined on an individual basis following the interview process, considering various factors such as years of experience, skills, education/certifications, contract specifications, market conditions, etc.
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Not a good fit? Check out our other opportunities: https://jobs.jobvite.com/visionistNext steps: Apply online and one of our recruiters will reach out to you. We have a streamlined process of phone screen with a recruiter, interview with a Visionist team at our HQ in Columbia, MD, and that is all!
Interested in learning more about Visionist and the work we do? Check out our website! https://www.visionistinc.com/what\-we\-do
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*U.S citizenship required (green card holders and permanent residents are not eligible). Applicants selected will be required to obtain / maintain a government security clearance.*
*Visionist, Inc. is an Equal Opportunity / Protected Veterans / Individuals with Disabilities employer.*
Salary Context
This $170K-$240K range is above the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Visionist, INC, 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 $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($205K) sits 6% below the category median. Disclosed range: $170K to $240K.
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.
Visionist, INC AI Hiring
Visionist, INC has 3 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Laurel, MD, US, Columbia, MD, US. Compensation range: $240K - $240K.
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 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 4,317 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).
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 4,317 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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