Interested in this AI Software Engineer role at Icon?
Apply Now →Skills & Technologies
About This Role
ICON is looking for a pragmatic builder who has made the leap from traditional software engineering into the emerging world of agentic AI development to join our Government Technology team. As an AI Software Engineer at ICON, you will be responsible for designing and shipping AI\-powered tools, workflows, and autonomous agents that accelerate ICON's construction technology platform. This role reports to the Senior Director, Defense Technology Programs and is a full\-time on\-site position based on our Austin, TX campus.
RESPONSIBILITIES
- Design and build agentic AI systems that automate complex, multi\-step workflows across ICON's software platform
- Develop LLM\-powered features and products using state\-of\-the\-art foundation models and APIs (e.g. Anthropic, OpenAI)
- Architect and implement multi\-agent pipelines, tool\-use systems, and Model Context Protocol (MCP) integrations
- Build robust RAG systems including document ingestion, chunking strategies, embedding pipelines, and vector retrieval
- Collaborate with software and domain teams to identify high\-leverage AI automation opportunities and translate them into shipped products
- Own the full development lifecycle of AI features: prototyping, evaluation, deployment, and iteration
- Serve as a technical resource and informal mentor on agentic AI best practices across the engineering organization
- Stay at the leading edge of the agentic AI landscape and bring emerging techniques into production
MINIMUM QUALIFICATIONS
- 8\+ years of professional software engineering experience with a strong foundation in backend or full\-stack development
- Demonstrated experience building and shipping production\-grade products using LLMs and agentic frameworks
- Proficiency in TypeScript and/or Python
- Deep understanding of prompt engineering, context management, and LLM reasoning patterns
- Experience with tool\-use, function calling, and agent orchestration (e.g. LangChain, LlamaIndex, Claude Code, or custom implementations)
- Proficiency in the design and execution of structured evals to measure and improve AI system performance
- Strong communication skills and comfort working cross\-functionally with both technical teams and non\-technical stakeholders
- Experience working in or alongside government, defense, or regulated environments
- Strong experience working with code generation agents (e.g. Claude Code, Cursor, Devin\-style systems)
PREFERRED SKILLS AND EXPERIENCE
- Experience with MCP (Model Context Protocol) server development and integration
- Familiarity with vector databases (e.g. pgvector, Pinecone, Weaviate)
- Experience with fine\-tuning, RLHF, or model evaluation pipelines
- Strong background in ML fundamentals: embeddings, transformers, attention mechanisms
- Exposure to structured output generation and LLM\-based data extraction
- Familiarity with AWS and serverless infrastructure for AI workloads
- Interest or background in the AEC (architecture, engineering, construction) industry
*ICON is an equal opportunity employer committed to fostering an innovative, inclusive, diverse and discrimination\-free work environment. Employment with ICON is based on merit, competence, and qualifications. It is our policy to administer all personnel actions, including recruiting, hiring, training, and promoting employees, without regard to race, color, religion, gender, sexual orientation, gender identity, national origin or ancestry, age, disability, marital status, veteran status, or any other legally protected classification in accordance with applicable federal and state laws. Consistent with the obligations of these laws, ICON will make reasonable accommodations for qualified individuals with disabilities.*
*Furthermore, as a federal government contractor, the Company maintains an affirmative action program which furthers its commitment and complies with recordkeeping and reporting requirements under certain federal civil rights laws and regulations, including Executive Order 11246, Section 503 of the Rehabilitation Act of 1973 (as amended) and the Vietnam Era Veterans' Readjustment Assistance Act of 1974 (as amended).*
*Headhunters and recruitment agencies may not submit candidates through this application. ICON does not accept unsolicited headhunter and agency submissions for candidates and will not pay fees to any third\-party agency without a prior agreement with ICON.*
*As part of our compliance with these obligations, the Company invites you to voluntarily self\-identify as set forth below. Provision of such information is entirely voluntary and a decision to provide or not provide such information will not have any effect on your employment or subject you to any adverse treatment. Any and all information provided will be considered confidential, will be kept separate from your application and/or personnel file, and will only be used in accordance with applicable laws, orders and regulations, including those that require the information to be summarized and reported to the federal government for civil rights enforcement purposes.*
Internet Applicant Employment Notices
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 Icon, 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. Senior-level AI roles across all categories have a median of $227,400.
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.
Icon AI Hiring
Icon has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Austin, TX, US.
Location Context
AI roles in Austin pay a median of $212,800 across 317 tracked positions. That's 16% above the national 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 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.