Manufacturing Process Engineer

Keystone Partners Consulting

Frederick (MD)

On-site

USD 120,000 - 170,000

Full time

3 days ago
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Job summary

Keystone Partners Consulting is seeking an engineer-focused professional who designs AI-powered workflows and automation pipelines to modernize business operations. The role bridges technical systems and business strategy, translating complex concepts for executives, collaborating with operations and engineering, and guiding vendors from requirements through delivery.

Ideal candidates hold a mechanical or electrical engineering degree, show a passion for AI/ML, and demonstrate structured problem

Qualifications

  • Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or a related discipline.
  • Interest in AI/ML, software tools, or a technical pivot.
  • Strong analytical and systems-thinking skills; can break down complex problems.
  • Comfort working with APIs and data analysis tools (SQL, Python, Excel).
  • Excellent communication skills for cross-team collaboration.

Responsibilities

  • Map existing operational and technical processes to identify automation and AI integration opportunities.
  • Design and deploy AI-powered workflows using tools like LLM APIs, RAG pipelines, and workflow automation platforms.
  • Translate complex technical concepts into clear roadmaps for non-technical stakeholders and executives.
  • Partner with engineering, operations, and leadership teams to prioritize high-impact use cases.
  • Apply structured problem-solving methodologies to evaluate and improve automation initiatives.
  • Manage vendor evaluations and technology integrations from requirements through delivery.

Skills

Systems thinking
Analytical skills
Communication
APIs familiarity
Data analysis

Education

Bachelor’s degree in Mechanical or Electrical Engineering

Tools

LLM platforms
Workflow automation platforms
APIs

Job description

We're looking for someone who thinks like an engineer and builds like a technologist. This role is ideal for a mechanical or electrical engineer who has developed a passion for AI, automation, and digital transformation — and wants to apply that rigorous, systems-based problem-solving to modern business operations.


You’ll bridge the gap between technical systems and business strategy, designing and implementing AI-driven workflows, automation pipelines, and data-informed solutions that directly improve operational efficiency.


What You’ll Do


  • Map existing operational and technical processes to identify automation and AI integration opportunities

  • Design and deploy AI-powered workflows using tools like LLM APIs, RAG pipelines, and workflow automation platforms

  • Translate complex technical concepts into clear roadmaps for non-technical stakeholders and executives

  • Partner with engineering, operations, and leadership teams to prioritize high-impact use cases

  • Apply structured problem-solving methodologies (root-cause analysis, process optimization, systems thinking) to evaluate and improve automation initiatives

  • Manage vendor evaluations and technology integrations from requirements through delivery


What We’re Looking For


  • Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or a related engineering discipline

  • Demonstrated interest in AI/ML, software tools, or a technical pivot (side projects, certifications, additional coursework, or on-the-job initiatives count)

  • Strong analytical and systems-thinking skills — you naturally break down complex problems into structured solutions

  • Comfort working with APIs, data analysis tools (SQL, Python, Excel), or workflow automation platforms is a plus

  • Excellent communication skills — able to work fluidly between technical teams and business stakeholders


Nice to Have


  • Experience with LLM platforms (Claude, ChatGPT, Copilot, Gemini) or prompt engineering

  • Six Sigma, Lean, or other process-improvement certification

  • Prior internship or project experience specifically in AI strategy, automation, or digital transformation

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