Interested in this AI Software Engineer role at General Dynamics Mission Systems?
Apply Now →Skills & Technologies
About This Role
Basic Qualifications :
Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. Also requires 5\+ years of job\-related experience, or a Master's degree plus 3 years of job\-related experience. Agile experience preferred.
Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position:
What You'll Do:* Conduct code reviews across the platform codebase. You will review pull requests thoroughly, provide clear and constructive feedback, and help maintain code quality standards.
- Build and maintain integrations with enterprise systems including SharePoint (via Microsoft Graph API), GitLab, EPDM, and internal Hub services.
- Develop and maintain LLM API integrations across multiple providers.
- Build and maintain RAG pipelines: document ingestion, parsing, chunking, embedding generation, vector database storage, and retrieval.
- Develop backend APIs in Python, including asynchronous request handling and background job processing.
- Contribute to agent framework development.
- Implement and maintain authentication and authorization flows.
- Troubleshoot and fix production issues.
- Collaborate with team on deployment, monitoring, and infrastructure needs.
- Mentor junior engineers through code review, pairing, and technical guidance.
Expected Skills:* Expert Python skills — you need to be an expert writing, reading, and reviewing Python.
- Experience building and consuming REST APIs
- Working experience with at least one major LLM API — token management, streaming responses, prompt construction, error handling
- Understanding of RAG patterns — embeddings, vector databases, document chunking and retrieval
- Experience with async programming or task queue systems
- Proficiency with Git and Docker usage
- Demonstrated ability to conduct thorough, constructive code reviews
What Sets You Apart:* Azure cloud experience
- SharePoint or Microsoft Graph API integration experience
- Kubernetes awareness
- PostgreSQL
- Experience with agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen, or similar)
- Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar)
Our Commitment to You:* An exciting career path with opportunities for continuous learning and development
- Flexible schedules with every other Friday off work, if desired (9/80 schedule)
- Competitive benefits, including 401k matching, flex time off, paid parental leave, healthcare benefits, health \& wellness programs, employee resource and social groups, and more
- See more at gdmissionsystems.com/careers/why\-work\-for\-us/benefits
Workplace Options:
This position allows you to be either fully remote/telework, fully on\-site, OR Hybrid/Flex at one of several facilities. Interviews:
We do not allow the use of AI during any step of the interview process.
Salary Note: This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled. Combined Salary Range: USD $124,397\.00 \- USD $138,003\.00 /Yr. Company Overview:
General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000\+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high\-performance team!
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans
Salary Context
This $124K-$138K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $189K across 518 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 26,159 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At General Dynamics Mission Systems, 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 $235,100 based on 665 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($131K) sits 44% below the category median. Disclosed range: $124K to $138K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
General Dynamics Mission Systems AI Hiring
General Dynamics Mission Systems has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span San Antonio, TX, US, Scottsdale, AZ, US, Remote, US. Compensation range: $138K - $203K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.