Artificial Intelligence Engineer
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use those headings if content exists.
We have:
- About the role: Could be the summary and company description? The summary: "As an AI Engineer I at Universal, you will design and develop scalable AI solutions..." That's more like responsibilities. But we can put company description under "About the role"? Might be okay.
Better: Use "About the role" for the summary and company overview? The instruction says we can use those headings; we need to include a section only when posting has real specific content for it.
We have content for:
- Responsibilities: "What You’ll Be Doing (Essential Duties)" list.
- Requirements: "Minimum Requirements" list.
- Skills: "Preferred Skills" list.
- Benefits: "Benefits" paragraph.
- Pay: "The salary range for this position is $66,000 – $88,333." That's specific, so we can include Pay section.
- Schedule: Not mentioned; we have Status: Full-Time/ Salaried Exempt. That's schedule info (full-time). Could we include Schedule? The posting says Status: Full-Time/ Salaried Exempt. That's schedule info. So we can include Schedule section with "Full-Time, Salaried Exempt". That's specific.
- Qualifications: Could be same as Requirements? Might be redundant. We could omit Qualifications if we already have Requirements. But we could include Qualifications for education etc. However we have Minimum Requirements includes education, etc. We could treat that as Qualifications. But we need to avoid duplicate sections. Probably better to have Requirements (minimum) and Skills (preferred). We'll not add Qualifications.
- About the role: We have company description and maybe summary. We'll include About the role with company description and summary.
Now we need to format:
About the role
... company description + summary ...
But we must not repeat job title as heading. The job title is "AI Engineer I". We'll not repeat. We need to preserve all substantive information. So include company description paragraph(s) and summary. We need to use- for any list of duties/requirements/benefits.
Benefits: we have a paragraph listing many benefits; we could turn into
- items. The instruction: Use
- for any list of duties/requirements/benefits. So we should convert benefits to list.
Similarly responsibilities list.
Minimum Requirements list.
Preferred Skills list.
Pay: we can put in
. Schedule: we can put in
. Now we need to strip boilerplate: Work Authorization Requirement, EOE, etc. Remove those. Also remove duplicated lines: "All applicants must be authorized to work in the United States." appears twice; we remove. Also remove "Position: AI Engineer I Location/Department: Richmond Headquarters/ Information Systems Status: Full-Time/ Salaried Exempt Reports To: AI Project Manager" maybe we can incorporate location etc? Not required to keep but we should preserve substantive info. Location/Department maybe not needed for sections but could be included in About the role? The instruction: preserve ALL substantive information; do not invent or summarize away detail. So we need to keep location, department, status, reports to. Where to put? Could be in About the role paragraph or a separate meta paragraph. Since we cannot create headings for minor metadata, we can fold into a short
. So we can add a paragraph after About the role maybe: "
Location: Richmond Headquarters, Information Systems. Status: Full-Time, Salaried Exempt. Reports to: AI Project Manager.
" That preserves. Now we need to ensure we don't include any boilerplate like "EOE M/F/Disabled/Vet Employer", "All applicants must be authorized to work in the United States." etc. Now craft HTML. Let's extract company description: "Universal Leaf Tobacco Company is the world’s leading supplier of premium leaf tobacco, with over 100 years of experience sourcing, processing, and delivering tobacco crops tailored to customer specifications. With operations spanning major tobacco-regions across five continents, we connect hundreds of thousands of farmers to global manufacturers through a reliable, transparent, and traceable supply chain. Our portfolio includes flue-cured, burley, oriental, and dark tobaccos, supported by deep agronomic expertise and advanced processing capabilities. Beyond the leaf, we offer value-added services such as customized blending, next-generation nicotine solutions, recycled by-products, and digital traceability tools that enhance efficiency and sustainability across the supply chain. Universal Leaf Tobacco is more than a supplier – we are a long-term partner committed to responsible sourcing, farmer support, and continuous innovation. By investing in agricultural communities and upholding the highest standards of quality and compliance, we help ensure a resilient tobacco supply for generations to come." Now summary: "As an AI Engineer I at Universal, you will design and develop scalable AI solutions that support business innovation and operational efficiency. You will contribute to the full lifecycle of AI systems—from prototyping and model training to performance testing and deployment. This role is ideal for early-career professionals with strong technical foundations and a passion for machine learning and big data technologies." We can combine. Now responsibilities list (What You’ll Be Doing): - Design and develop scalable solutions using AI tools and machine learning models. - Ensure the scalability, reliability, and performance of AI systems across diverse use cases. - Develop and execute performance tests to evaluate system efficiency in handling large datasets, complex algorithms, and processing speeds. - Perform research and testing to develop machine learning algorithms and predictive models. - Utilize big data computation and storage tools to create prototypes and datasets. - Conduct model training, evaluation, and tuning to optimize performance. - Integrate, test, and monitor AI solutions in collaboration with cross-functional teams. - Document technical workflows and contribute to knowledge sharing across the team. - Stay current with emerging AI tools and technologies to support continuous improvement. Now Minimum Requirements list: - Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. - Proficiency in programming languages such as .net, Python, or R. - Internship or project experience in AI/ML (demonstrates hands-on exposure) - Basic understanding of statistics and data analysis - Experience with SQL or NoSQL databases - Ability to write clean, maintainable code and follow coding standards - Strong analytical and problem-solving skills. - Effective communication and collaboration abilities. - Typically reports to the AI Project Manager. (Actually that's not a requirement but a reporting line; we already captured reports to. Might keep as part of meta.) We could keep that line in meta. Now Preferred Skills list: - Exposure to MLOps tools and practices. - Experience with RESTful APIs or microservices - Familiarity with containerization (Docker) - Experience working in Agile/Scrum environments - Experience with data visualization and version control (e.g., Power-BI, Git). Now Benefits list: we need to parse the sentence: "We offer a wide range of market-competitive total rewards that include 401(k) match, pension, merit increases, paid holidays, medical, dental, life, vision, short and long-term disability benefits, and tuition assistance to name a few." We can make list items: 401(k) match, pension, merit increases, paid holidays, medical, dental, life, vision, short and long-term disability benefits, tuition assistance. Now Pay: "$66,000 – $88,333." Now Schedule: "Full-Time, Salaried Exempt". Now location/department/reports to: we already have meta. Now produce HTML. We must not include or . Just fragment. Let's construct:About the role
Universal Leaf Tobacco Company is the world’s leading supplier of premium leaf tobacco, with over 100 years of experience sourcing, processing, and delivering tobacco crops tailored to customer specifications. With operations spanning major tobacco-regions across five continents, we connect hundreds of thousands of farmers to global manufacturers through a reliable, transparent, and traceable supply chain. Our portfolio includes flue-cured, burley, oriental, and dark tobaccos, supported by deep agronomic expertise and advanced processing capabilities. Beyond the leaf, we offer value-added services such as customized blending, next-generation nicotine solutions, recycled by-products, and digital traceability tools that enhance efficiency and sustainability across the supply chain. Universal Leaf Tobacco is more than a supplier – we are a long-term partner committed to responsible sourcing, farmer support, and continuous innovation. By investing in agricultural communities and upholding the highest standards of quality and compliance, we help ensure a resilient tobacco supply for generations to come.
As an AI Engineer I at Universal, you will design and develop scalable AI solutions that support business innovation and operational efficiency. You will contribute to the full lifecycle of AI systems—from prototyping and model training to performance testing and deployment. This role is ideal for early-career professionals with strong technical foundations and a passion for machine learning and big data technologies.
Location: Richmond Headquarters, Information Systems. Status: Full-Time, Salaried Exempt. Reports to: AI Project Manager.
Responsibilities
- Design and develop scalable solutions using AI tools and machine learning models.
- Ensure the scalability, reliability, and performance of AI systems across diverse use cases.
- Develop and execute performance tests to evaluate system efficiency in handling large datasets, complex algorithms, and processing speeds.
- Perform research and testing to develop machine learning algorithms and predictive models.
- Utilize big data computation and storage tools to create prototypes and datasets.
- Conduct model training, evaluation, and tuning to optimize performance.
- Integrate, test, and monitor AI solutions in collaboration with cross-functional teams.
- Document technical workflows and contribute to knowledge sharing across the team.
- Stay current with emerging AI tools and technologies to support continuous improvement.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
- Proficiency in programming languages such as .net, Python, or R.
- Internship or project experience in AI/ML (demonstrates hands-on exposure)
- Basic understanding of statistics and data analysis
- Experience with SQL or NoSQL databases
- Ability to write clean, maintainable code and follow coding standards
- Strong analytical and problem-solving skills.
- Effective communication and collaboration abilities.
Skills
- Exposure to MLOps tools and practices.
- Experience with RESTful APIs or microservices
- Familiarity with containerization (Docker)
- Experience working in Agile/Scrum environments
- Experience with data visualization and version control (e.g., Power-BI, Git)
Benefits
- 401(k) match
- pension
- merit increases
- paid holidays
- medical
- dental
- life
- vision
- short and long-term disability benefits
- for any list of duties/requirements/benefits. So we should convert benefits to list.
Similarly responsibilities list.
Minimum Requirements list.
Preferred Skills list.
Pay: we can put in
- items. The instruction: Use