Intelligence Brief Engineering Sector
Controls Engineer
Controls engineers design and implement automated systems and control processes that enhance manufacturing efficiency and product quality. They work primarily in industries such as manufacturing, aerospace, and energy, w…
- $100,000
- Median salary
- 5%
- Projected growth
- 47/100
- Difficulty
- Bachelor's
- Min. education
Executive Summary
- Controls Engineer scores 53/100 (C), reflecting a challenging profile relative to other careers.
- Median salary of $100,000 reflects competitive earning potential.
- Projected growth of 5% is below the national average.
- AI resilience score of 72 suggests low automation risk — the role requires human judgment that AI cannot easily replicate.
Controls Engineer scores 53/100 — C. The strongest dimension is salary (50/100), followed by remote potential (40/100). The biggest challenge: job growth (18/100).
Research Insights
- At Risk
Future-proof
Controls Engineer faces significant headwinds for long-term viability (49/100). Projected growth of 5% is below the national average. Professionals should develop differentiated skills that AI cannot easily replicate.
Score 49 /100 - Moderate
Social Mobility
Controls Engineer offers moderate social mobility potential (46/100). Earnings are competitive, but the path is accessible with the right credentials.
Score 46 /100 - Below Average
Long-Term Outcomes
Controls Engineer faces headwinds for long-term positive outcomes (46/100). Slower-than-average job growth suggest that professionals in this field should plan for potential transitions or significant skill evolution over the next decade.
Score 46 /100
Economic Importance
Controls engineers play a critical role in optimizing automation processes across various industries, enhancing productivity and efficiency. Their expertise supports sectors like manufacturing, energy, and transportation, which are vital to economic stability and growth.
Role Analysis
What a Controls Engineer Does
Controls engineers design and implement automated systems and control processes that enhance manufacturing efficiency and product quality. They work primarily in industries such as manufacturing, aerospace, and energy, where precision and reliability are critical. These engineers analyze system performance, develop control algorithms, and program controllers to ensure that machinery operates smoothly.
The typical work environment for a controls engineer is a combination of office and hands-on settings, often requiring collaboration with other engineers, technicians, and production staff. Individuals who thrive in this role are analytical thinkers with strong problem-solving skills and a keen attention to detail. They enjoy working on complex systems and have a passion for technology and automation.
A Day in the Life
- Design control systems for automated machinery and processes.
- Program PLCs (Programmable Logic Controllers) and other control devices.
- Conduct tests and simulations to evaluate system performance.
- Troubleshoot and resolve issues in existing control systems.
- Collaborate with cross-functional teams to improve processes.
- Document control system designs and operational procedures.
- Stay updated with advancements in control technologies.
Compensation Structure
By Experience Level
- Entry level
- $60,000 - $75,000
- Mid-career
- $85,000 - $110,000
- Senior / experienced
- $110,000 - $130,000
By Company Size
| Company | Base | Bonus | Equity | Total |
|---|---|---|---|---|
| Small business / Startup | $60,000 - $75,000 | $1,000 - $5,000 | $0 - $10,000 | $61,000 - $90,000 |
| Mid-market | $85,000 - $110,000 | $2,000 - $10,000 | $0 - $15,000 | $87,000 - $135,000 |
| Large corporate | $100,000 - $120,000 | $5,000 - $20,000 | $0 - $25,000 | $105,000 - $165,000 |
| Enterprise / Public company | $110,000 - $130,000 | $5,000 - $25,000 | $0 - $30,000 | $115,000 - $185,000 |
Compensation tends to increase with company size, reflecting greater resources and potential for complex projects. Larger firms often offer more comprehensive benefits and equity options.
Outlook · 5% growth
The demand for controls engineers is expected to grow by 5% over the next decade, driven by the increasing reliance on automation in various industries. This growth indicates a steady need for skilled professionals who can design, implement, and maintain control systems to enhance operational efficiencies.
Career Pathways
The trajectory to Controls Engineer varies by entry point and specialization. Below are the most common paths, typical timelines, and advancement probabilities.
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Traditional Path
Obtain a Bachelor's Degree → Gain Relevant Experience → Develop Technical Skills → Obtain Professional Certification → Network with Professionals → Target Role: Senior Controls Engineer- Timeline
- 5-10 years
- Advancement probability
This path is effective for those who follow a structured educational and professional development route.
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Alternative Path through Certifications
Obtain a Bachelor's Degree → Obtain Professional Certification → Gain Relevant Experience → Develop Technical Skills → Target Role: Mid-Career Controls Engineer- Timeline
- 4-8 years
- Advancement probability
Certifications can expedite career advancement if combined with relevant experience.
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Lateral Move from Related Fields
Obtain a Bachelor's Degree in a related field → Gain relevant experience in another engineering role → Transition to Controls Engineering → Develop Technical Skills → Target Role: Controls Engineer- Timeline
- 3-7 years
- Advancement probability
Professionals from related fields can leverage their skills to transition into controls engineering with appropriate training.
Common Credentials
- Certified Automation Professional (CAP)
- Control Systems Technician (CST)
Skill Stack
The Controls Engineer skill set operates across four layers. Differentiator skills (marked) are the competencies that most strongly predict advancement to this role.
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Foundation
- Basic programming skills
- Understanding of control theory
- Familiarity with CAD software
- Basic troubleshooting skills
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Intermediate
- Proficiency in C/C++ or Python
- Experience with PLC programming
- Ability to design HMIs
- Understanding of industrial automation
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Advanced
- Expertise in control systems design
- Advanced data analysis skills
- Experience with robotics
- Project management skills
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Differentiating
Differentiator- Innovative problem-solving
- Leadership in cross-functional teams
- Ability to mentor junior engineers
Scorecard Analysis
Our proprietary scorecard evaluates careers across five dimensions from BLS wage and growth data, O*NET work context, and standard education requirements. The blended difficulty score reflects the combined challenge across all metrics.
Moderate earning potential
Below-average growth
Moderate education barrier
Limited remote options
Moderate competition
Career Difficulty Score
47/100
Controls Engineer offers limited remote work options.
AI Resilience Assessment
Our AI Resilience score estimates how likely a career is to be disrupted by artificial intelligence. Scores are based on a category baseline adjusted by keyword analysis of job duties. A score of 70+ means low automation risk; 50\u201369 means moderate risk; below 50 means high risk.
- Requires complex human judgment and cross-disciplinary problem-solving that AI cannot replicate.
- Domain expertise and contextual decision-making create a moat against full automation.
- Limited risk: Routine analytical or documentation tasks may be partially automated.
AI Verdict
Controls Engineer ranks highly for AI resilience. The role demands complex human judgment, specialized expertise, or physical presence that AI cannot easily replicate. Professionals who stay current with AI tooling in their domain will remain in strong demand.
Risk Factors & Failure Modes
Understanding where professionals stall or fail to reach this role is as important as knowing the path. Below are the most common bottlenecks.
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Lack of continuous skill development can lead to obsolescence in a rapidly evolving field.
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Inadequate experience in real-world applications may hinder job performance and advancement.
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Poor networking can limit opportunities for career growth and mentorship.
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Failure to obtain professional certifications may restrict advancement to higher-level positions.
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Inability to adapt to new technologies can result in reduced competitiveness in the job market.
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Weak communication skills may lead to misunderstandings in multidisciplinary teams.
Controls Engineer Archetypes
There is no single profile for a Controls Engineer. Professionals reach this role through different backgrounds, each bringing distinct strengths and limitations.
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Industrial Controls Engineer
Focused on automating manufacturing processes, this archetype often collaborates with production teams to enhance system performance.
Strengths
- Deep understanding of industrial automation
- Proficiency in PLC programming
- Ability to troubleshoot complex systems
- Strong collaboration skills
Weaknesses
- Limited exposure to software development
- May struggle with project management
- Narrow focus on specific industries
Best fit: Manufacturing plants and production facilities
-
Robotics Controls Engineer
This archetype specializes in designing and programming robotic systems, often working in cutting-edge technology environments.
Strengths
- Expertise in robotics and control theory
- Innovative problem-solving skills
- Strong coding abilities
- Experience with HMI design
Weaknesses
- Potentially high-pressure deadlines
- Requires continuous learning to keep up with advancements
- May face isolation in highly technical roles
Best fit: Research and development labs or robotics firms
-
Systems Integration Engineer
Focusing on integrating various control systems, this archetype ensures seamless communication between hardware and software components.
Strengths
- Strong analytical skills
- Ability to design complex systems
- Experience with CAD software
- Excellent communication skills
Weaknesses
- Can be overwhelmed by system complexities
- May need to balance multiple projects
- Requires good negotiation skills
Best fit: Consulting firms or large corporations with diverse systems
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Automated Testing Engineer
This archetype concentrates on developing automated testing protocols for control systems, ensuring reliability and performance.
Strengths
- Attention to detail
- Strong programming skills
- Ability to analyze test data
- Experience with quality assurance processes
Weaknesses
- May have repetitive tasks
- Limited interaction with other teams
- Requires specialized knowledge of testing tools
Best fit: Quality assurance departments or tech firms
Decision Intelligence
Beyond the numbers: assessing fit, risk, and realistic expectations for this career path.
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Personality Fit
Individuals who thrive in structured environments and enjoy problem-solving will excel as controls engineers, while those who prefer unstructured or highly creative roles may find this career challenging.
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Risk Tolerance Required
The career offers moderate risk, as job stability is generally solid but can fluctuate with economic cycles affecting industrial sectors.
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Work-Life Reality
Controls engineers typically enjoy a balanced work-life schedule, though project deadlines may occasionally lead to extended hours.
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Cognitive Demands
This role requires high cognitive engagement, with an emphasis on systems thinking, data analysis, and the ability to navigate ambiguous situations.
Feeder Degrees
Controls Engineers come from a variety of educational backgrounds. Below are the most common degrees held by professionals in this field, ranked by median salary.
- 1Computer ScienceBachelor's 4 years OnlineTop schools: MIT, Stanford University, Carnegie Mellon University$132,270Median25%Much faster than average
- 2Electrical EngineeringBachelor's 4 yearsTop schools: MIT, Stanford University, UC Berkeley$108,170Median5%Faster than average
- 3Mechanical EngineeringBachelor's 4 yearsTop schools: MIT, Stanford University, Georgia Tech$99,510Median10%Faster than average
Institutions With Strong Outcomes
Institutions with meaningful programs in Engineering, Technology, ranked by median graduate earnings 10 years after enrollment.
- 1 Massachusetts Institute of Technology MA · 96% graduate $143,372 Median earnings
- 2 Harvey Mudd College CA · 93% graduate $138,687 Median earnings
- 3 University of Health Sciences and Pharmacy in St. Louis MO · 69% graduate $137,047 Median earnings
- 4 Franklin W Olin College of Engineering MA · 94% graduate $129,455 Median earnings
- 5 California Institute of Technology CA · 94% graduate $128,566 Median earnings
- 6 Stanford University CA · 92% graduate $124,080 Median earnings
Where Controls Engineers Get Hired
Graduates who become Controls Engineers frequently land at employers like Amazon, Microsoft, Apple and Google. Each profile below shows the schools that feed it, the degrees that lead there, and its current hiring momentum.
Amazon
Technology · Technology
Microsoft
Technology
Apple
Technology
Technology
Dell
Technology
Adobe
Technology
Methodology & Data Sources
Salary and growth data sourced from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) and Employment Projections program. Education requirements and work context derived from O*NET. AI Resilience scores are proprietary, based on category baselines adjusted by keyword analysis of job duties against current AI capability benchmarks. Pipeline probabilities and compensation by company size are modeled estimates synthesized from executive compensation surveys and industry research. Degree and school outcome data sourced from the U.S. Department of Education College Scorecard and Opportunity Insights. Editorial intelligence sections (archetypes, risk factors, decision intelligence) are research-based assessments, not predictive models.
Data Behind This Page Updated 2025
Source datasets
Methodology
Careers are scored on five normalized axes — salary, job growth, AI resilience, education barrier, and competition — each on a 0–100 scale, with composite Future-Proof, ROI, and breadth verdicts.
See the full methodology and weights →Confidence notes
- Salary and growth figures come from federal Bureau of Labor Statistics data — administrative wage records and official projections, not surveys.
- AI-resilience scores are computed from O*NET task and work-context data, applied consistently across every occupation.
- Every measure is normalized to a fixed 0–100 scale, so careers are directly comparable.
Limitations
- BLS wage data reflect national medians; actual pay varies widely by region, employer, and experience.
- Job growth is a 2023–2033 projection, not a guarantee — labor markets shift with technology and the economy.
- AI-resilience is a directional estimate of automation exposure, not a prediction that any role will or will not be automated.
- Pipeline and compensation-by-company-size figures are modeled estimates, not measured outcomes.
