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Business Operations Engineer Jobs (NOW HIRING)

FHLBank Pittsburgh

DevOps Engineer

Pittsburgh, PA · On-site

$51.25 - $70.25/hr

... s Engineer supports the delivery of modern, secure, and scalable technology solutions by combining ... serve multiple business units and ensuring secure, reliable software release processes. As a ...

Fhlbpgh

DevOps Engineer

Pittsburgh, PA

$51.25 - $70.25/hr

... s Engineer supports the delivery of modern, secure, and scalable technology solutions by combining ... multiple business units and ensuring secure, reliable software release processes. As a ...

Serigor, Inc.

Sr DevOps Engineer (Hybrid)

Baltimore, MD · On-site

$129.20K - $165.90K/yr

The expectation is that the ideal candidate will decompose the business processes, develop a stabilization strategy, and execute the resultant plans to completion. The Sr DevOps Engineer will ...

Texas Children's Hospital

Data Operations Engineer

Houston, TX · On-site +1

$66.40K - $89.80K/yr

Leads business analysis, information acquisition, data access design, archive and recovery strategy ... Operations Engineer or related occupation. In the alternative, Employer will accept a master ...

EliseAI

Platform Operations Engineer

New York, NY · On-site

$76K - $102.80K/yr

This role will operate at the intersection of business strategy and technology and serve as a ... Engineering and Data, to maximize adoption and operational efficiency * Act as a subject matter ...

Texas Children's Hospital

Data Operations Engineer

Houston, TX · On-site

$66.40K - $89.80K/yr

Leads business analysis, information acquisition, data access design, archive and recovery strategy ... Operations Engineer or related occupation. In the alternative, Employer will accept a master ...

Lunar Outpost

Senior Operations Engineer

Arvada, CO · On-site

$71.20K - $96.30K/yr

As an Operations Engineer you will be responsible for helping to maintain and improve Lunar Outpost ... Identify, develop, and execute improvement opportunities to enable business scalability * Work with ...

NABORS

Business Operations Associate

Houston, TX

By leveraging its core competencies, particularly in drilling, engineering, automation, data ... business operations, analytics, project coordination, finance, or similar roles. * Strong ...

SpaceX

Operations Engineer (Space Planning)

Hawthorne, CA · On-site

$110K - $135K/yr

OPERATIONS ENGINEER (SPACE PLANNING) The Corporate Operations Engineering team supports overall business operations through strategic planning, optimization of processes, and alignment of resources ...

Business Integra

DevOps Engineer

San Jose, CA · On-site

$61.75 - $84.75/hr

... s Engineer Location: San Jose, CA Duration: 1+ years contract or permanent/fulltime Key words to look for: • Experience with Puppet, Chef and Ansible • Experience of deploying applications like ...

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$135K

How much do business operations engineer jobs pay per year?

As of Jun 1, 2026, the average yearly pay for business operations engineer in the United States is $85,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,500.00 and $94,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Business Operations Engineer, you need strong analytical skills, process optimization expertise, and a background in business, operations, or engineering—often supported by a relevant degree. Familiarity with data analysis tools (like SQL, Excel, or Tableau), process mapping software, and experience with ERP or workflow management systems is typically expected. Excellent problem-solving abilities, communication skills, and an aptitude for cross-functional collaboration set outstanding candidates apart. These competencies are vital for streamlining operations, driving efficiency, and ensuring business objectives are met effectively.

How do Business Operations Engineers typically collaborate with other departments to improve processes?

Business Operations Engineers work closely with cross-functional teams such as IT, finance, sales, and product management to identify inefficiencies and develop solutions that streamline operations. They often facilitate meetings to gather input, analyze workflow bottlenecks, and implement process improvements using data-driven insights. Effective communication and the ability to translate technical recommendations into actionable steps for various departments are essential for success in this role.

What are Business Operations Engineers?

Business Operations Engineers are professionals who bridge the gap between business processes and technical systems within an organization. They analyze workflows, identify inefficiencies, and implement solutions—often involving automation or software tools—to optimize business performance. Their role typically includes collaborating with cross-functional teams, managing data, and ensuring that business operations run smoothly and efficiently. Business Operations Engineers help organizations adapt to changing needs by designing and improving processes for scalability and productivity.

What is the difference between Business Operations Engineer vs Business Analyst?

AspectBusiness Operations EngineerBusiness Analyst
Required credentialsBachelor's in Business, Engineering, or related field; technical skills often preferredBachelor's in Business, Finance, or related field; analytical skills essential
Work environmentCross-functional teams, technical and operational settingsData analysis, reporting, and process improvement teams
Employer usageTech companies, startups, manufacturing firmsConsulting firms, finance, corporate departments
Common search intentUnderstanding technical and operational rolesAnalyzing business processes and data

Business Operations Engineers focus on optimizing technical and operational systems within organizations, often requiring technical skills and engineering knowledge. Business Analysts primarily analyze data and business processes to recommend improvements. While both roles support business efficiency, their core responsibilities and skill sets differ, making this comparison useful for those exploring career options or job opportunities.

What cities are hiring for Business Operations Engineer jobs? Cities with the most Business Operations Engineer job openings:
What states have the most Business Operations Engineer jobs? States with the most job openings for Business Operations Engineer jobs include:
What job categories do people searching Business Operations Engineer jobs look for? The top searched job categories for Business Operations Engineer jobs are:
Business Operations Engineer jobs near you
Infographic showing various Business Operations Engineer job openings in the United States as of May 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 75% Physical, 6% Hybrid, and 19% Remote job distribution, with an average salary of $85,029 per year, or $40.9 per hour.
AI Engineer, Business Operations

AI Engineer, Business Operations

Sk Life Science, Inc.

Paramus, NJ • On-site

$70.30K - $95.10K/yr

Full-time

Posted 6 days ago

Job description

Overview
The AI Engineer, Biz Ops will build the AI-powered services that form the backbone of our decision-intelligence platform. In this role, you will take AI models developed by AI Scientists and transform them into scalable, production-ready applications by designing inference pipelines, APIs, and supporting data flows.
You will work closely with Data Engineers to integrate model pipelines with the broader data ecosystem and collaborate with business operations and commercial teams to convert manual, step-driven workflows into AI-native services. This includes building reliable batch and real-time inference systems that generate measurable impact across business operations-not limited to any specific domain.
This is a high-impact role for engineers who enjoy turning research into products, hardening systems for real-world use, and building the engineering layer that enables AI to operate at scale. While not required, an interest in or exposure to MLOps practices is strongly preferred.
Responsibilities
  • Productionize AI/ML models into scalable services (e.g., APIs, batch inference, streaming inference) with strong standards for reliability and performance.
  • Collaborate with AI Scientists to convert research prototypes into production-ready components (feature computation, preprocessing, post-processing, evaluation loops).
  • Integrate models with data pipelines built by Data Engineers and ensure seamless end-to-end flow from raw data to AI-driven output.
  • Build and maintain inference pipelines using Python and orchestration frameworks (e.g., Airflow), supporting deployment across cloud and on-prem environments.
  • Implement CI/CD, containerization, and automated testing to ensure safe, repeatable, and automated model deployments.
  • Establish monitoring and observability for models and services (system metrics, data drift, performance regression, alerting).
  • Partner with BizOps and Commercial stakeholders to transform manual workflows into AI-enabled services that improve operational decision-making.
  • Optimize end-to-end model serving latency, throughput, and cost using packaging strategies, scaling policies, caching, and parallelization.
  • Contribute to documentation, reusable templates, and engineering best practices to accelerate AI adoption across the organization.

Qualifications
  • Education: Bachelor's degree or higher in Computer Science, Engineering, or related technical field.
  • Experience: 3+ years of software engineering experience, including building or deploying AI systems in production environments.
  • Skills:
    • Strong proficiency in Python for services, pipelines, and ML tooling.
  • Experience deploying AI models in production across on-prem or cloud environments (AWS or Azure).
  • Experience with big-data and orchestration frameworks (e.g., Spark, Airflow) for scalable pipelines.
  • Strong understanding of software engineering best practices including CI/CD, containerization (Docker, Kubernetes), automated testing, and version control.
  • Experience with model optimization techniques such as ONNX / ONNX Runtime, model quantization, or other performance-oriented inference tooling.

Strongly Preferred
  • Interest or exposure to MLOps concepts (model registries, feature stores, experiment tracking, automated retraining, monitoring).
  • Master's degree or higher in a relevant field.
  • Experience in regulated industries (e.g., biopharma, healthcare, and finance).
  • A portfolio of launched AI/ML projects or contributions to production of AI systems.
  • Proficiency in SQL and familiarity with modern data warehouses such as Snowflake.

Who Thrives in This Role
  • Engineers who enjoy transforming research into resilient, user-facing products.
  • Builders who balance rapid iteration with production-grade engineering standards.
  • Collaborators who can partner with business teams to convert manual workflows into scalable AI services.
  • Pragmatic problem-solvers who can operate autonomously and drive impact in ambiguous, cross-functional settings.

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