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About This Role
CONSTRUCT YOUR CAREER WITH MEARS AND BUILD AMERICA'S FUTURE
Are you looking for your next big opportunity? At Mears Group we offer more than just a job. We offer a career where you can grow, innovate, and make a real impact.
Mears Group, Inc., a Quanta Services company, is a leader in the construction and infrastructure industry. With more than 50 years of experience, we are committed to safety, quality, and integrity. We bring together people and resources to build the framework that powers our nation.
Senior Software Engineer – AI Applications
We're looking for an experienced software engineer who enjoys solving business problems through modern software development and practical applications of AI. You'll design and build enterprise applications that leverage technologies such as Azure OpenAI, Microsoft Copilot, ChatGPT, Claude, and other AI services to automate processes, improve productivity, and deliver measurable business value. The ideal candidate is a strong software engineer first, with experience integrating AI into production applications—not someone focused solely on experimental models or research.
WHY JOIN MEARS?
- Build America:Mears is a leading provider of engineering and construction solutions in oil and gas, electric transmission and distribution, telecom, and wastewater industries across North America.
- Professional growth: Mears offers comprehensive training programs and career advancement pathways.
- Competitive compensation:Enjoy competitive wages and excellent benefits.
- Community impact:We give back to the communities we serve.
SAFETY THAT BRINGS YOU HOME:
At Mears, safety is our utmost priority. We are at the forefront of enhancing safety outcomes for both our employees and clients. We empower our workers to take ownership of their own safety. The Capacity Model is designed to minimize the risk of accidents and injuries.
BENEFITS \& COMPENSATION:
Despite our size, Mears remains a family company. Our suite of benefits reflects our commitment to our employees.
- Salary info: $100,000\.00 to $120,000\.00 per year, paid semi\-monthly
- Job type: full time
- Paid on\-the\-job technical and professional growth opportunities
- Established career path for future advancement
- 401k and Roth 401(k) retirement savings plans
- Health, prescription, dental, vision plans
- Life \& Disability Insurance plans
- Financial wellness program
- Employee assistance program
- Employee discount programs
WHO WE’RE LOOKING FOR:
We're looking for engineers who build production\-quality software and use AI as a tool to solve business problems. The ideal candidate has strong software engineering fundamentals, experience delivering enterprise applications, and practical experience incorporating modern AI capabilities into production systems.
ESSENTIAL DUTIES:
- Design, develop, test, and maintain enterprise software applications.
- Build AI\-enabled business solutions using modern LLM platforms and cloud services.
- Collaborate with business stakeholders to identify automation opportunities.
- Integrate enterprise systems using APIs and cloud technologies.
- Develop secure, scalable, and maintainable software following engineering best practices.
- Mentor junior developers through code reviews and technical guidance.
- Evaluate emerging AI technologies and recommend practical adoption.
- Support deployment, monitoring, and continuous improvement of production applications.
- Contribute to engineering standards, documentation, and CI/CD practices.
- Perform other duties as assigned.
KEY QUALIFICATIONS:
- Bachelor's degree in Computer Science, Software Engineering, or equivalent experience.
- Cloud certifications such as Microsoft Azure AI Engineer, AWS Machine Learning Specialty, or equivalent preferred
- MLOps or Data Engineering certifications preferred
- 5\+ years of professional software development experience.
- Proficiency in Python, object\-oriented programming (OOP), modular design, and test\-driven development (TDD).
- AI/ML Frameworks: Expertise in PyTorch and/or TensorFlow for model development, training, and deployment.
- Experience building enterprise web applications, APIs, and cloud solutions.
- Experience with Microsoft Azure (preferred) or AWS.
- Experience integrating AI platforms such as Azure OpenAI, OpenAI, Claude, Gemini, or Microsoft Copilot.
- Experience with SQL, REST APIs, Git, automated testing, and CI/CD.
- Data Engineering: Strong skills with SQL/NoSQL databases, ETL workflows, data pipelines, and tools like Apache Airflow and Apache Spark.
- Vector Databases \& RAG: Experience with Pinecone, FAISS, or Weaviate for retrieval\-augmented generation and contextual AI.
- Advanced AI Techniques: Proficiency in fine\-tuning, parameter\-efficient tuning (PEFT), transfer learning, low\-rank adaptation (LoRA), reinforcement learning, and RAG pipelines.
- Enterprise Systems: Familiarity with Spectrum, HCSS, Oragami, Prophix, Onestream, Power BI, Cozys, Primavera P6, Incorta, or Bid2Win.
- Strong communication, collaboration, and problem\-solving skills.
- The physical activity and work environment for this role includes
+ Travel as needed
+ Standing, sitting and walking for prolonged periods of time in an office environment
+ Manual dexterity in the use of computers and other equipment
+ Lift and carry office equipment
- Pass pre\-employment drug screen and background check
This role is accepting applications until November 30th
This position is subject to the Federal Department of Transportation (DOT) drug \& alcohol testing regulations as outlined in 49 CFR Part 382 and/or 49 CFR Part 199\.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Equal Opportunity Employer, including disabled and veterans.
Salary Context
This $100K-$120K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Mears Group 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 $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($110K) sits 50% below the category median. Disclosed range: $100K to $120K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Mears Group Inc AI Hiring
Mears Group Inc has 2 open AI roles right now. They're hiring across AI Software Engineer. Based in Englewood, CO, US. Compensation range: $80K - $120K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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