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About This Role
Company Description
DevIQ specializes in building modern cloud and data solutions – and we believe in the power of software and technology to improve lives. Join us to partner with passionate mid\-market companies focused on reducing energy costs, curing disease, improving education, building smart cities, and more. From true innovation and synergetic cloud \& technology partnerships to competitive full\-time benefits and a strong team culture, DevIQ is a great place to work.
At DevIQ, you’ll:
- Build your career with a supportive, inclusive team that appreciates people, creates value, embraces growth, and “owns the problem” as a team.
- Enjoy opportunities to learn, exposure to new industries, and building end\-to\-end solutions through meaningful work on active client projects.
- Work remotely and/or from our modern studio in downtown Denver.
- Bring your unique perspective and experience to multi\-disciplinary teams.
- Collaborate on and contribute to transformative digital experiences that touch millions of lives, watching your work make an impact.
Please note that you must be a U.S. citizen or eligible to work in the U.S. to be considered for this role, and third\-party candidates will not be accepted.
Job Description
We’re looking for a hands\-on Lead AI\-Native Software Engineer to help shape how we build software in the age of agentic AI. This role blends technical leadership, AI\-accelerated delivery, and client\-facing consulting, with meaningful hands\-on time spent designing and shipping solutions alongside the team. You’ll use agentic AI tools such as Claude Code and Codex as a core part of your daily workflow, and you’ll raise the bar for how our teams and our clients build software with them.
Key Responsibilities:
- Lead the architecture, design, and implementation of modern software solutions for clients, serving as the senior technical voice on consulting engagements
- Use agentic AI tools (Claude Code, Codex, Cursor, or similar) as a primary development workflow, delegating implementation, testing, and refactoring tasks to agents while maintaining rigorous quality standards
- Design codebases to be agent\-friendly, with clear conventions, strong automated test coverage, and documentation that enables AI tooling to work effectively
- Establish review and verification practices for AI\-generated code, ensuring correctness, security, and maintainability in everything the team ships
- Build and maintain prompts, custom agents, and CI/CD integrations that automate routine engineering work across client projects
- Serve as a trusted advisor to clients, communicating complex technical concepts clearly to both technical and non\-technical stakeholders, setting realistic expectations, and building lasting relationships
- Listen actively and empathetically to client needs, asking thoughtful questions and translating business goals into pragmatic technical roadmaps
- Mentor and coach engineers on AI\-native development practices, raising the velocity and quality of every team you work with
- Partner with sales and leadership on pre\-sales activities, including technical discovery, solution design, and estimating
- Foster a collaborative, inclusive team culture, giving and receiving feedback constructively, navigating disagreement respectfully, and owning the problem as a team
- Evaluate emerging AI development tools and patterns and decide which earn a place in the stack
Qualifications Required:
- 8\+ years of professional software engineering experience, including experience leading technical teams or serving as a technical lead
- Real\-world, production experience using agentic AI coding tools (such as Claude Code, Codex, or Cursor) to accelerate software delivery, beyond autocomplete\-style assistance
- Prior consulting or customer service experience with a track record of success working directly with external clients or customers
- Strong expertise in at least one modern language and ecosystem (such as TypeScript/Node, Python, C\#/.NET, or Java) and experience delivering on at least one major cloud platform (AWS or Azure)
- Deep grounding in software engineering fundamentals, including architecture, automated testing, CI/CD, and code review, and the judgment to know when to trust agent output and when to inspect it closely
- Exceptional communication skills, including the ability to explain technical trade\-offs to non\-technical audiences, facilitate meetings, present with confidence, and write clearly
- Strong interpersonal skills, including empathy, active listening, patience, and professionalism under pressure
- Adaptability and curiosity, with a demonstrated habit of learning rapidly evolving tools and helping others do the same
Preferred:
- Experience supporting pre\-sales efforts (architecture, scoping, solutioning, estimating) preferred
- Experience building agentic workflows and infrastructure, such as MCP servers, custom agents, prompt libraries, or AI\-assisted CI pipelines
- Experience driving adoption of AI development practices across a team or organization, including measuring impact on velocity and quality
- Experience with conflict resolution, stakeholder management, or formal customer\-facing roles in a professional services environment
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience
Additional Information
Est. Salary Range (Colorado Only): $140,000\-$175,000\*
- Disclaimer: In accordance with Colorado’s Equal Pay for Equal Work Act, effective January 1, 2021, a good faith hourly or base salary range must be posted for all positions where the work may be performed in the state of Colorado. Therefore, this good faith salary range will only apply where this described position will be performed in the state, and should not be considered the compensation range in other locations or for other positions.
DevIQ Benefits Include:
- Competitive financial compensation and utilization bonus plans
- Medical, Dental, Vision Insurance
- 401k, With 4% Matching
- Paid Time Off
- Health Savings Account (HSA)/Flexible Spending Account (FSA)
- Short\-Term/Long\-Term Disability Insurance
- Business funded Life Insurance Plan
- Dynamic yet relaxed work atmosphere
- Wide Variety of Growth Opportunities
Salary Context
This $140K-$175K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 219 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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At DevIQ, 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 $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($157K) sits 32% below the category median. Disclosed range: $140K to $175K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
DevIQ AI Hiring
DevIQ has 2 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Denver, CO, US. Compensation range: $170K - $175K.
Location Context
AI roles in Denver pay a median of $184,000 across 159 tracked positions. That's 8% below 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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