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About This Role
At Jabil (NYSE: JBL), we are proud to be a trusted partner for the world's top brands, offering comprehensive engineering, supply chain, and manufacturing solutions. With 60 years of experience across industries and a vast network of over 100 sites worldwide, Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe.
JOB SUMMARY
This position will lead the identification, evaluation, design, development, and deployment of Artificial Intelligence (AI) and intelligent automation solutions across Jabil's Indirect Procurement Technology landscape. The role will partner closely with business stakeholders to assess opportunities for process optimization, develop AI agents and automation solutions, define solution architectures, and support the organization's AI strategy and roadmap.
Our ideal candidate is an innovative, process\-oriented problem solver with a passion for emerging technologies and digital transformation. The successful candidate will combine strong business acumen with technical aptitude to deliver scalable AI and automation solutions that improve operational efficiency, user experience, and business outcomes.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Identify , evaluate, and prioritize opportunities to leverage Artificial Intelligence, intelligent automation, and digital technologies to improve business processes and operational efficiency.
- Partner with business stakeholders to analyze current\-state processes, define future\-state solutions, and develop automation strategies aligned with organizational objectives .
- Design solution architectures for AI agents, workflow automations, and intelligent business solutions utilizing enterprise technologies, APIs, and automation platforms.
- Develop, configure, test, deploy, and maintain AI agents, prompt\-driven solutions, scripts, and workflow automations supporting the Indirect Procurement Technology portfolio.
- Apply prompt engineering best practices to optimize Large Language Model (LLM) performance, agent behavior, and business outcomes.
- Evaluate business use cases and determine the most appropriate solution approach utilizing Artificial Intelligence, Robotic Process Automation (RPA), APIs, scripting, workflow automation, or traditional system enhancements.
- Contribute to the development and execution of the organization's AI strategy and technology roadmap by researching emerging capabilities, evaluating vendor solutions, and recommending scalable approaches.
- Develop business cases and success metrics for automation initiatives, measuring adoption, operational improvements, efficiency gains, and return on investment.
- Collaborate with business process owners, application administrators, developers, and integration teams to deliver end\-to\-end automation solutions.
- Create technical documentation, solution designs, support procedures, and knowledge articles for developed solutions.
- Support user adoption through demonstrations, training, change management activities, and ongoing operational support.
- Continuously monitor emerging AI technologies, automation capabilities, and industry best practices to identify opportunities for innovation.
- Comply, follow, and enforce all procedures within the company security policy.
- May perform other duties and responsibilities as assigned.
JOB QUALIFICATIONS \& KNOWLEDGE REQUIREMENTS
- Bachelor's degree in Information Systems , Computer Science, Business, Engineering, Data Analytics, or a related discipline.
- Experience identifying , designing, or implementing AI, automation, workflow optimization, or digital transformation initiatives.
- Strong understanding of business process analysis, process improvement methodologies, and solution architecture principles.
- Experience developing AI agents, intelligent workflows, scripts, macros, API integrations, or Robotic Process Automation (RPA) solutions, or demonstrated aptitude and strong interest in developing these capabilities.
- Working knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and agent\-based workflows.
- Experience with enterprise applications, automation platforms, scripting languages, SQL, or integration technologies is preferred.
- Ability to evaluate business requirements and determine appropriate technical solutions balancing complexity, scalability, maintainability, and business value.
- Strong analytical, problem\-solving, project management, and organizational skills.
- Ability to communicate effectively with both technical and business stakeholders at all organizational levels.
- Ability to create technical documentation, procedural manuals, and end\-user training materials.
- Ability to manage multiple priorities while working independently in a fast\-paced environment.
- Demonstrated curiosity, continuous learning mindset, and passion for emerging AI technologies and innovation.
- Preferred experience with the following software: Coupa, SAP, ServiceNow, WalkMe, BluePrism
The pay range for this role is $79,400 \- $142,900\. Job\-related, non\-discriminatory factors used to determine the actual offered rate include qualifications and experience, geographic location, education, external market data, and consideration of internal equity. The anticipated close date of this job requisition is: September 30, 2026\.
As part of the total rewards package, this position is eligible for a short\-term incentive based on performance. In addition, Jabil offers benefits to enhance your health, wealth, and resilient self. These include medical, dental, and vision insurance plans; paid time off accruing at a rate of 3\.07 hours during your first year of employment; 4 weeks of paid parental leave; in 2026, 11 company\-paid holidays (9 fixed holidays and 2 optional floating holidays), subject to change yearly; 401(k) retirement plan; and employee stock purchase plan.
BE AWARE OF FRAUD: When applying for a job at Jabil you will be contacted via correspondence through our official job portal with a jabil.com e\-mail address; direct phone call from a member of the Jabil team; or direct e\-mail with a jabil.com e\-mail address. Jabil does not request payments for interviews or at any other point during the hiring process. Jabil will not ask for your personal identifying information such as a social security number, birth certificate, financial institution, driver’s license number or passport information over the phone or via e\-mail. If you believe you are a victim of identity theft, contact the Federal Bureau of Investigations internet crime hotline (www.ic3\.gov), the Federal Trade Commission identity theft hotline (www.identitytheft.gov) and/or your local police department. Any scam job listings should be reported to whatever website it was posted in.
Jabil, including its subsidiaries, is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, age, disability, genetic information, veteran status, or any other characteristic protected by law.
Accessibility Accommodation
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If you are a qualified individual with a disability, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access Jabil.com/Careers site as a result of your disability. You can request a reasonable accommodation by sending an e\-mail to Always\[email protected] or calling 727\-803\-7988 with the nature of your request and contact information. Please do not direct any other general employment related questions to this e\-mail or phone number. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to.
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Salary Context
This $79K-$142K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Jabil, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($111K) sits 48% below the category median. Disclosed range: $79K to $142K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Jabil AI Hiring
Jabil has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Saint Petersburg, FL, US. Compensation range: $142K - $142K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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