AI System Developer III

Primary purpose:

The AI System Developer III serves as a senior individual contributor responsible for the design, development, integration, and support of complex AI-enabled solutions, enterprise integrations, and advanced microservices. This role operates with a high degree of independence and contributes to solution design decisions, reusable architectural patterns, and the technical maturity of the AI Center of Excellence. The position emphasizes deep expertise across retrieval-augmented generation (RAG), multi-agent orchestration, and model fine-tuning, while accelerating enterprise delivery through AI-assisted development and mentoring of less experienced team members.

Tallgrass was named one of the Top Workplaces USA and highlighted in Colorado''s Top Workplaces for the past seven consecutive years. Tallgrass is a leading energy infrastructure company focused on safely, reliably, and sustainably delivering the energy and services that power our nation and enable our quality of life.

At Tallgrass, we value our teams and strive to create an environment where employees feel respected, and their contributions are valued. We aim to support employees'' physical, mental, and financial well-being through a comprehensive Total Rewards Program.

• Industry competitive pay
• Health insurance package options that include Flexible Spending & Health Savings Accounts
• Infertility Coverage
• Parental Leave
• 401(k) with up to a 6% match that vests immediately plus an employer discretionary contribution of up to 4%
• Wellness Programs and Mental Health Resources
• Employer-paid life insurance, short-term disability, and long-term disability coverage
• Critical Illness & Accident Insurance
• Vacation, sick days, paid caregiver leave, volunteer and bereavement paid time off
• Identity theft protection
• Annual discretionary bonus
• Generous Tuition Reimbursement Program
• Company-paid holidays and floating holidays
• Company vehicle (if applicable)
• Employee discounts; vehicles, tires, cellular plans, and more
• Networking and employee engagement events
• Personal development to grow your career with us based on your strengths and interests

Application Deadline: Recruiting timelines vary by position; however, all Tallgrass positions accept applications for at least five business days from the posting date. This position is open and still accepting applications.

Compensation: Compensation ranges are provided in good faith based on what we anticipate when researching wages for this position at the state and national levels. We may ultimately pay more or less than the posted range. This salary range may also be modified in the future.

Notice to External Search Firms: Tallgrass does not accept unsolicited resumes from search firms or employment agencies. Unsolicited referrals and resumes are considered Tallgrass property; therefore, Tallgrass will not pay a fee for any placement resulting from the receipt of an unsolicited referral. Approved vendors may be invited to refer talent for specific positions at Tallgrass''s request only. A fully executed agreement with Tallgrass must be in place and current in these cases.

EEO Statement: Tallgrass complies with all Equal Employment Opportunity (EEO) affirmative action laws and regulations. Tallgrass does not discriminate on the basis of age, race, religion, color, sex, national origin, marital status, genetic information, sexual orientation, gender Identity and expression, disability, veteran status, pregnancy status, or other status protected by law.

Education:

• Bachelor''s degree from an accredited institution in Computer Science, Machine Learning, Data Science, Software Engineering, Information Systems, Business Management, or a related discipline. A Master''s degree in Computer Science, Machine Learning, or a related field is preferred.
• A minimum of seven (7) years of direct work experience in IT or a related discipline may be considered as a substitute for a degree.

Experience/Specific Knowledge:

• Minimum of four (4) to five (5) years of overall IT experience.
• Minimum of four (4) years of recent experience focusing on system development, support, implementation, and upgrades with demonstrated AI/ML components.
• Minimum of four (4) years of development experience in modern software engineering languages and environments; strong proficiency in Python and common ML/AI libraries and frameworks required.
• Demonstrated hands-on experience deploying and optimizing LLMs (open-source or API-based) in production environments.
• Demonstrated experience designing and implementing RAG solutions including vector store selection, embedding pipelines, and retrieval quality tuning.
• Demonstrated experience designing and implementing agentic or multi-agent systems using orchestration libraries and frameworks.
• Experience with model fine-tuning, instruction-tuning, or domain adaptation including training data preparation and evaluation.
• Experience in the full product development life cycle including design contribution, development, testing, deployment, and post-production support.
• Established SQL skills in MS SQL and/or Oracle databases and working knowledge of data engineering patterns.
• Experience with reporting tools and the ability to develop and maintain operational and audit reports.
• Experience in an application development environment using web frameworks, microservices, Microsoft .NET or equivalent technology.
• Experience implementing AI security controls including PII handling, prompt injection defense, content moderation, and output validation.
• Experience effectively communicating business and technical issues to both technical and non-technical audiences.
• Experience managing multiple assignments with competing priorities with minimal supervision.
• Advanced proficiency in MS Office applications including but not limited to Excel, Word, Access, PowerPoint, and Outlook.

Certifications, Licenses & Registrations:

• Must possess and maintain a valid driver''s license and a driving record satisfactory to the company and its insurers (for travel).
• Application Developer certification(s) such as MCSD, OCP/M/E, CSD, or equivalent preferred. AI/ML certifications or advanced training from recognized vendors or community programs strongly preferred.

Competencies, Skills & Abilities:

• Ability to work independently with minimal supervision and collaboratively in a team environment; share knowledge, mentor peers, and accept direction from management.
• Ability to manage multiple tasks and competing priorities under strict deadlines; organize work and use time efficiently.
• Deliver excellent customer service and maintain professional relationships across all levels of the organization.
• Demonstrated ability to communicate clearly, both verbally and in writing, technical and systems requirements to both technical and non-technical stakeholders.
• Ability to contribute to solution design discussions, evaluate technical trade-offs, and recommend practical approaches within the scope of assigned work.
• Use analytical and technical understanding of complex AI systems to diagnose problems and identify efficient, practical solutions.
• Demonstrated ability to mentor and provide constructive feedback to less experienced team members through code review and technical guidance.
• Demonstrate strong attention to detail, reliability, and adherence to work schedules and policies.
• Able to perform the essential functions of the position.

Physical Demands:

All the physical requirements listed below are those that may be necessary for an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made for individuals with disabilities to perform the essential functions.

• Must be able to sit for prolonged periods of time.
• The employee is regularly required to use hands to type, touch, handle, or feel. The employee is required to talk and hear. The employee is frequently required to stand and reach with hands and arms. The employee is occasionally required to walk and climb or balance. The employee must regularly lift and/or move up to 10 pounds and occasionally lift and/or move up to 25 pounds.

Working Conditions:

• Required to carry a cell phone and be available to respond during working and non-working hours.
• The successful candidate will be required to clear a drug screen and a complete background check, including credit report for certain positions, after an offer has been extended and prior to being employed.

Supervisory Responsibility:

• None. This role provides informal technical mentorship and peer code review but carries no formal supervisory or people management responsibility.

Preferred Education, Experience, Certifications, Competencies, Skills & Abilities:

Above the minimum requirements, not required but advantageous in this position:

• Master''s degree in Computer Science, Machine Learning, Data Science, or a related field.
• Advanced hands-on experience with fine-tuning or instruction-tuning LLMs for domain-specific enterprise applications.
• Experience with advanced multi-agent frameworks including agent memory architectures, tool-use patterns, and failure recovery strategies.
• Experience with AI red teaming, adversarial testing, or formal AI security evaluation methodologies.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud-native ML services and pipelines.
• Experience with advanced vector database configurations, hybrid search strategies, and RAG evaluation frameworks.
• Experience with containerization and orchestration at scale or cloud-managed equivalents.
• Contributions to open-source AI/ML projects, technical publications, or community knowledge sharing.

Compensation:

• The annual salary range for this position will be $106,000-$131,000/yr.

Other responsibilities:

• The above statements describe the general nature and level of work being performed. This position may perform other duties as assigned.

Essential duties and responsibilities:

• Design, implement, and optimize retrieval-augmented generation (RAG) solutions including vector store design, knowledge index management, chunking strategies, embedding model selection, and retrieval quality evaluation.
• Contribute to the design and implementation of multi-agent systems, agentic call flows, and LLM fine-tuning and adaptation for domain-specific use cases; includes agent-to-agent communication patterns, tool use, memory management, training data preparation, and model evaluation.
• Design, implement, and maintain complex AI system components including model serving APIs, advanced inference pipelines, and production-grade microservices.
• Implement and optimize integrations between LLMs, AI services, and enterprise applications including internal portals, chatbots, and workflow automation platforms.
• Apply and contribute to AI governance guardrails and security controls including data minimization, PII detection and redaction, prompt injection mitigation, content moderation, adversarial input handling, and model output validation; collaborate with Legal, Compliance, and Security to implement controls required for regulatory frameworks and internal policy adherence.
• Translate complex business requirements into technical specifications, flow diagrams, solution designs, and implementation plans with minimal supervision.
• Work with Data & Analytics to define, access, and prepare AI-ready datasets; ensure data quality, lineage, and appropriate transformations for model training and inference workloads.
• Contribute to and improve CI/CD pipelines, containerization strategies (Docker/Kubernetes), model versioning, model registry practices, and MLflow workflows to support reliable and repeatable AI delivery.
• Write and review unit, integration, and acceptance tests for AI components and APIs; contribute to evaluation framework improvements; participate in release planning, deployment verification, and post-deployment monitoring; troubleshoot complex production issues, perform root-cause analysis, and implement durable fixes or mitigations; provide on-call support as required.
• Mentor Level I and Level II developers through code review and technical guidance; create and maintain technical documentation, runbooks, and API documentation; support business stakeholders with training and adoption playbooks; and contribute reusable patterns, templates, and components to the Center of Excellence knowledge base.
• Create and maintain comprehensive technical documentation, runbooks, user guides, and API documentation for engineering and business audiences.
• Perform all duties with tact, courtesy, and professionalism; work effectively across multi-disciplinary teams; maintain regular, dependable attendance and a high regard for personal safety, company assets, and the general public; and perform other duties as assigned.

Essential duties and responsibilities:

• Design, implement, and optimize retrieval-augmented generation (RAG) solutions including vector store design, knowledge index management, chunking strategies, embedding model selection, and retrieval quality evaluation.
• Contribute to the design and implementation of multi-agent systems, agentic call flows, and LLM fine-tuning and adaptation for domain-specific use cases; includes agent-to-agent communication patterns, tool use, memory management, training data preparation, and model evaluation.
• Design, implement, and maintain complex AI system components including model serving APIs, advanced inference pipelines, and production-grade microservices.
• Implement and optimize integrations between LLMs, AI services, and enterprise applications including internal portals, chatbots, and workflow automation platforms.
• Apply and contribute to AI governance guardrails and security controls including data minimization, PII detection and redaction, prompt injection mitigation, content moderation, adversarial input handling, and model output validation; collaborate with Legal, Compliance, and Security to implement controls required for regulatory frameworks and internal policy adherence.
• Translate complex business requirements into technical specifications, flow diagrams, solution designs, and implementation plans with minimal supervision.
• Work with Data & Analytics to define, access, and prepare AI-ready datasets; ensure data quality, lineage, and appropriate transformations for model training and inference workloads.
• Contribute to and improve CI/CD pipelines, containerization strategies (Docker/Kubernetes), model versioning, model registry practices, and MLflow workflows to support reliable and repeatable AI delivery.
• Write and review unit, integration, and acceptance tests for AI components and APIs; contribute to evaluation framework improvements; participate in release planning, deployment verification, and post-deployment monitoring; troubleshoot complex production issues, perform root-cause analysis, and implement durable fixes or mitigations; provide on-call support as required.
• Mentor Level I and Level II developers through code review and technical guidance; create and maintain technical documentation, runbooks, and API documentation; support business stakeholders with training and adoption playbooks; and contribute reusable patterns, templates, and components to the Center of Excellence knowledge base.
• Create and maintain comprehensive technical documentation, runbooks, user guides, and API documentation for engineering and business audiences.
• Perform all duties with tact, courtesy, and professionalism; work effectively across multi-disciplinary teams; maintain regular, dependable attendance and a high regard for personal safety, company assets, and the general public; and perform other duties as assigned.