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Wind Engineer Jobs in Colorado (NOW HIRING)

IPL (Indiana)

Project Manager, Wind

Louisville, CO · On-site

Lead, manage, and facilitate project delivery with teams of project engineering, commissioning ... Familiarity with wind project design and technical standards as well as civil and structural ...

The AES Corporation

Civil Engineer

Louisville, CO · On-site

Experience with wind, PV systems and BESS ranging from 500 kW to 200+ MW is preferable. While civil engineering is the primary qualification, the role will require the review of information related ...

Vestas Wind Systems

Repair Manager

Brighton, CO · On-site

$110K - $130K/yr

Experience in wind, large scale manufacturing or aerospace required * Technical background in mechanical, composites, or electrical engineering * Certifications in Lean Six Sigma, (Green Belt or ...

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Wind Engineer information

See Colorado salary details

$11

$37

$66

How much do wind engineer jobs pay per hour?

As of Jun 30, 2026, the average hourly pay for wind engineer in Colorado is $37.62, according to ZipRecruiter salary data. Most workers in this role earn between $28.51 and $40.50 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Wind Engineer, and why are they important?

To thrive as a Wind Engineer, you need a strong background in mechanical, civil, or electrical engineering, often supported by a relevant degree and experience in renewable energy projects. Familiarity with CAD software, wind resource assessment tools, and industry standards like IEC 61400 is typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and stakeholders. These skills and qualifications enable Wind Engineers to design, optimize, and implement efficient wind energy solutions while ensuring safety and regulatory compliance.

What is the difference between Wind Engineer vs Wind Turbine Technician?

AspectWind EngineerWind Turbine Technician
Required CredentialsBachelor's degree in engineering or related field; often professional engineering licenseTechnical diploma or associate degree; specialized training
Work EnvironmentDesign, analysis, project planning; office and field site visitsOn-site maintenance, troubleshooting, and repairs at wind farms
Employer & Industry UsageWind energy companies, engineering firms, project developersWind farm operators, maintenance service providers

Wind Engineers focus on designing and planning wind energy projects, requiring engineering credentials and working in both office and field environments. Wind Turbine Technicians primarily perform maintenance and repairs on turbines, working directly on-site. Both roles are essential in the wind energy industry but differ in responsibilities and required qualifications.

What are some common challenges Wind Engineers face when planning new wind farm projects?

Wind Engineers often encounter challenges such as accurately assessing wind resources, navigating complex environmental regulations, and coordinating with multiple stakeholders including landowners, utility companies, and local authorities. Site selection can be particularly demanding due to considerations like terrain, wildlife impact, and grid connectivity. Effective communication and problem-solving skills are essential, as Wind Engineers must collaborate closely with multidisciplinary teams to balance technical, environmental, and economic factors throughout the project lifecycle.

What does a Wind Engineer do?

A Wind Engineer specializes in the design, analysis, and implementation of wind energy systems, primarily focusing on wind turbines and wind farms. They assess potential sites for wind energy generation, analyze wind patterns, and ensure that wind turbines are efficiently and safely installed and maintained. Wind Engineers also work on optimizing turbine performance, minimizing environmental impact, and complying with regulations. Their work plays a crucial role in advancing renewable energy and reducing reliance on fossil fuels.
What are popular job titles related to Wind Engineer jobs in Colorado? For Wind Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Wind Engineer jobs in Colorado look for? The top searched job categories for Wind Engineer jobs in Colorado are:
Wind Engineer jobs near you

Blades - Digital Engineering & AI Specialist

Envision Energy

Boulder, CO • On-site

$115K - $150K/yr

Full-time

Posted 6 days ago

Job description

About the Global Blade Innovation Center
Envision Energy's Global Blade Innovation Center (GBIC) was established in 2015 to build a world-class, in-house blade design capability. Engineers from industry-leading OEMs, national laboratories, and top graduate programs have collaborated to create a state-of-the-art design capability from the ground up. Envision's in-house blade designs and technologies have disrupted global markets and delivered significant reductions in Levelized Cost of Energy (LCOE) alongside measurable expansion of Envision's market share.
The wind industry is at an inflection point in how engineering work gets done. GBIC is investing in the AI and digital engineering capabilities needed to stay at the leading edge, and this role is the architect of that effort.
The Role
As the Digital Engineering & AI Specialist, you will define, own, and execute the high-level architecture of AI systems and tools that transform how the Blade Design team operates. This is not an implementation support role. You will determine what gets built, how it is structured, and how it connects to real engineering workflows. You will design and deploy AI agents, automation pipelines, and intelligent decision-support systems that make the team faster, more consistent, and capable of solving problems at a scale and speed not otherwise possible.
This role requires equal command of the engineering domain and the AI/software toolkit. You need enough structural and wind engineering intuition to identify where AI can have genuine impact, and the technical depth to architect and build systems that engineers trust and use.
Key Responsibilities
AI Architecture & System Design
  • Define the high-level architecture of AI tools and systems for the Blade Design and Engineering teams, including agent frameworks, orchestration layers, data pipelines, and model integration patterns.
  • Own the end-to-end AI development lifecycle: problem framing, system design, model selection and development, validation, deployment, and iteration.
  • Design multi-agent systems and agentic workflows that automate complex, multi-step engineering tasks, from inspection data processing to RCA support to design evaluation.
  • Establish standards, patterns, and reusable components for AI-assisted engineering work products across the team.
    AI/ML Model Development & Deployment
  • Develop, fine-tune, and deploy AI/ML models for blade engineering applications including defect detection and classification; failure mode prediction; structural performance surrogate modeling; and manufacturing quality assessment.
  • Apply physics-informed and domain-constrained modeling approaches where engineering knowledge can improve model reliability and generalizability.
  • Validate AI/ML outputs rigorously against physical test data, field observations, and engineering expectations. Model confidence must be earned, not assumed.
  • Build model monitoring and feedback loops that allow deployed systems to improve over time with new engineering data.
    Engineering Automation & Workflow Integration
  • Identify and automate high-friction engineering workflows across blade design, reliability, and field operations, including analyses pipelines, inspection processing, reporting, and data aggregation.
  • Build and maintain internal engineering tools, APIs, and platforms that directly integrate AI capabilities into day-to-day engineering practices.
  • Collaborate with IT and data infrastructure teams to ensure engineering data is structured, accessible, and AI-ready.
  • Support structural health monitoring and in-service data applications as one domain where AI tools add high value, including anomaly detection, damage identification, and condition-based monitoring.
    Domain Collaboration & Technical Leadership
  • Work closely with composite design and field reliability engineers to understand physical failure modes and translate domain knowledge into effective AI system architecture and model design.
  • Communicate AI system capabilities, limitations, and outputs clearly to engineering stakeholders, earning trust through transparency, not just performance metrics.
  • Champion responsible AI adoption within the team: clear validation standards, documented assumptions, and traceable outputs.
  • Stay at the leading edge of AI/ML for engineering applications; evaluate and introduce relevant advances in agentic AI, LLM tooling, and applied ML to the team
    Qualifications Required
  • MS or PhD in Mechanical, Aerospace, Civil, or Structural Engineering, Computer Science, or a closely related field, with demonstrable wind or structural engineering domain knowledge.
  • 5+ years of professional experience at the intersection of engineering and applied AI/ML or digital systems development and deployment.
  • Demonstrated experience designing and deploying AI/ML systems for engineering or industrial applications, including system architecture decisions, not just model training.
  • Experience building agentic AI systems, multi-agent frameworks, or LLM-integrated engineering workflows.
  • Strong programming proficiency in Python; experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Working knowledge of composite blade or wind turbine structural behavior sufficient to evaluate whether model outputs are physically plausible.
  • Proven ability to communicate complex technical concepts clearly across engineering, operations, and leadership audiences.
    Strongly Valued
  • Experience with data pipeline development, signal processing, or time-series analysis in structural or condition monitoring contexts (e.g., SHM, NDT data, drone inspection imagery).
  • Familiarity with LLM orchestration frameworks (LangChain, LlamaIndex, or similar) and prompt engineering applications.
  • Background in physics-informed neural networks (PINNs) or other approaches that embed domain knowledge into model architecture.
  • Experience with FEA/FEM tools (ANSYS, ABAQUS, or similar) and ability to use simulation data as AI/ML training input.
  • Experience building internal engineering software platforms, REST APIs, or analytical dashboards used by engineering teams in production.
  • Background in wind energy OEM, operator, or research environments.
    What We're Looking For
    The ideal candidate thinks about systems. You don't just build models; you design the architecture that makes a team of engineers more capable than they could be alone. You are energized by the gap between what AI can theoretically do and what gets trusted and used in engineering practice, and you know how to close it. You have the domain credibility to earn the confidence of experienced blade engineers, and the technical range to move from agentic framework design to model validation to deployment in a single week.
    Strong interpersonal, collaboration, and communication skills are essential. Envision's culture is entrepreneurial and fast-moving; the ability to move between deep technical work and cross-functional collaboration is expected. Desire and ability to work effectively across cultural boundaries and international time zones is critical.
    Work Arrangement & Travel
  • Work arrangement: Hybrid
  • Travel: Up to 15% international travel, including field deployments and collaboration with global GBIC teams.

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