# Computer Hardware Engineers

> Research, design, develop, or test computer or computer-related equipment for commercial, industrial, military, or scientific use. May supervise the manufacturing and installation of computer or computer-related equipment and components.

- **SOC code:** 17-2061.00
- **Canonical URL:** https://singulariki.com/roles/role-17-2061-00
- **Also known as:** Design Engineer, Engineer, Hardware Engineer, Systems Integration Engineer, Field Service Engineer, Hardware Design Engineer, Physical Design Engineer, Project Engineer
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Update knowledge and skills to keep up with rapid advancements in computer technology.
- Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives.
- Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system.
- Build, test, and modify product prototypes, using working models or theoretical models constructed with computer simulation.
- Write detailed functional specifications that document the hardware development process and support hardware introduction.
- Test and verify hardware and support peripherals to ensure that they meet specifications and requirements, by recording and analyzing test data.
- Direct technicians, engineering designers or other technical support personnel as needed.
- Provide technical support to designers, marketing and sales departments, suppliers, engineers and other team members throughout the product development and implementation process.
- Select hardware and material, assuring compliance with specifications and product requirements.
- Store, retrieve, and manipulate data for analysis of system capabilities and requirements.
- Analyze user needs and recommend appropriate hardware.
- Evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Computers and Electronics _(knowledge)_
- Engineering and Technology _(knowledge)_
- Design _(knowledge)_
- Mathematics _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Information Ordering _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Writing _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Active Learning _(Common Skill)_
- Linux _(Specialized Skill)_

**Tools & technology:**
- C _(hot technology, in demand)_
- C++ _(hot technology, in demand)_
- Linux _(hot technology, in demand)_
- Perl _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- The MathWorks MATLAB _(hot technology, in demand)_
- Apache Subversion SVN _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- Git _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 88th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 80th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 79th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 91st percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 34th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 7.3% growth (Growing fast); 4.7k annual openings; 76.8k → 82.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $155,020; 75,710 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 43% automation, 52% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Store, retrieve, and manipulate data for analysis of system capabilities and requirements. _(21.5% of measured AI use; directive)_
- Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications. _(19.5% of measured AI use; learning)_
- Write detailed functional specifications that document the hardware development process and support hardware introduction. _(1.2% of measured AI use; task iteration)_
- Evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration. _(0.9% of measured AI use; learning)_
- Analyze user needs and recommend appropriate hardware. _(0.8% of measured AI use; directive)_
- Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system. _(0.8% of measured AI use; learning)_
- Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives. _(0.3% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me store, retrieve, and manipulate data for analysis of system capabilities and requirements.
- Help me analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications.
- Help me write detailed functional specifications that document the hardware development process and support hardware introduction.
- Help me evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration.
- Help me analyze user needs and recommend appropriate hardware.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-17-2061-00_