Principal Software Engineer – AI & Software Factory Engineering

$113K - $154K Remote Senior AI Software Engineer

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Skills & Technologies

DockerKubernetesPythonRag

About This Role

AI job market dashboard showing open roles by category

Clearance Level

None

Category

Software Engineering

Location

Remote, Working from the USA

Key Skills For Success

Containerization Software

GitLab CI/CD

Kubernetes Orchestration

Software Delivery

##### REQ\#:RQ225967

##### Public Trust:None

##### Requisition Type:Regular

##### Your Impact

Own your opportunity to support our nation's defense. Make an impact by connecting and securing critical operations across the globe, keeping our country safe and secure.

Job Description

-------------------

Principal Software Engineer – AI \& Software Factory Engineering

We're looking for a software engineer who likes building platform products — the tooling, automation, and AI capabilities other engineering teams build on top of. You'll write production code daily on a small, senior team delivering software factories, security automation, and AI\-enabled development environments for Department of War and Federal customers. If your instinct when you see a manual process is to write code that eliminates it, this role is built for you.

MEANINGFUL WORK AND PERSONAL IMPACT

You'll work across multiple concurrent R\&D and customer delivery efforts rather than a single narrow program, with the option to engage in proposals and customer demos if you want to build business acumen alongside technical depth

  • Build agentic AI capabilities — tool orchestration, LLM application development, and workflow automation — using AI\-assisted development daily
  • Develop software that automates continuous Authority to Operate (cATO): evidence collection, compliance reporting, and policy\-as\-code enforcement
  • Build secure\-by\-default CI/CD pipeline products — hardening templates, integrated security scanning (SAST, SCA, container, SBOM), and supply chain controls (signing, provenance, attestation) — that development teams across our portfolio consume
  • Extend the platform with self\-service capabilities: developer onboarding automation, reusable deployment patterns, and AI development tools (code assistants, model serving) — including for air\-gapped environments
  • Ship to and support production on hardened Kubernetes (Big Bang / Iron Bank) in CUI/IL5 environments — we run what we build

WHAT YOU’LL NEED TO SUCCEED

  • Education: Bachelor's degree and 8\+ years experience. In lieu of degree 12\+ years of hands\-on experience
  • Experience: 5\+ years of related experience in Software Engineering, DevOps / DevSecOps technologies; 3\+ years of hands on experience with Kubernetes
  • Strong development skills in Python, Go, or similar — you build tooling and applications, not just configure them
  • Daily use of AI\-powered development tools (code assistants, LLM\-based tooling)
  • CI/CD pipeline development — GitLab CI strongly preferred; Jenkins, GitHub Actions, or similar accepted
  • Security scanning integration in automated pipelines (SAST, DAST, SCA, container scanning)
  • Containerization (Docker, Helm, OCI artifacts) and Infrastructure as Code (Terraform and/or Ansible)
  • Git\-based workflows, GitOps deployment patterns, and solid Linux fundamentals
  • Experience working in or deploying to classified or air\-gapped environments
  • Strong written and verbal communication; comfort juggling multiple projects with shifting priorities
  • Security clearance level: No clearance required to start with ability to obtain and mantain a Secret clearance
  • Location: Remote with travel up to 10%
  • Citizenship: US Citizenship

PREFERRED QUALIFICATIONS

  • Hands\-on experience with agentic AI frameworks or LLM APIs (tool\-use patterns, orchestration, RAG)
  • Platform One / Big Bang, Iron Bank, or DoW\-hardened Kubernetes distributions
  • DoW security and authorization frameworks (NIST 800\-53, RMF, cATO)
  • Software supply chain security practices (Sigstore/Cosign, Syft, in\-toto)
  • AI/ML infrastructure in enterprise or air\-gapped environments (model serving, GPU scheduling on K8s)
  • Certified Kubernetes Application Developer (CKAD) certification
  • Supporting proposals, RFI responses, or customer engagements as a technical SME

GDIT IS YOUR PLACE

At GDIT, the mission is our purpose, and our people are at the center of everything we do.

  • Growth: AI\-powered career tool that identifies career steps and learning opportunities
  • Support: An internal mobility team focused on helping you achieve your career goals
  • Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
  • Community: Award\-winning culture of innovation and a military\-friendly workplace

OWN YOUR OPPORTUNITY

Explore a career in software development at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your dedication to advancing innovation.

### Work Requirements

Years of Experience

8 \+ years of related experience

  • may vary based on technical training, certification(s), *or* degree

Certification

Travel Required

Less than 10%

Citizenship

U.S. Citizenship Required

### Salary and Benefit Information

The likely salary range for this position is $113,900 \- $154,100\. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

### Our Identity Verification Process

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

### About Our Work

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50\+ countries worldwide, offering leading mission\-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc.

*Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans*

Salary Context

This $113K-$154K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).

Role Details

Title Principal Software Engineer – AI & Software Factory Engineering
Location Remote, US
Category AI Software Engineer
Experience Senior
Salary $113K - $154K
Remote Yes

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 General Dynamics Information Technology, 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

Docker (10% of roles) Kubernetes (13% of roles) Python (52% of roles) Rag (21% of roles)

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 ($134K) sits 39% below the category median. Disclosed range: $113K to $154K.

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.

General Dynamics Information Technology AI Hiring

General Dynamics Information Technology has 13 open AI roles right now. They're hiring across Data Scientist, Data Engineer, AI/ML Engineer, AI Software Engineer. Positions span Remote, US, Arlington, VA, US, Chantilly, VA, US. Compensation range: $154K - $287K.

Remote Work Context

Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.

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

Based on 729 roles with disclosed compensation, the median salary for AI Software Engineer positions is $218,500. Actual compensation varies by seniority, location, and company stage.
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.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
General Dynamics Information Technology is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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