AI System Developer I

Tallgrass•Lakewood, CO

1d•Onsite

About The Position

The AI System Developer I serves as an entry-level individual contributor responsible for supporting the design, development, integration, and maintenance of AI-enabled solutions, enterprise integrations, and related microservices under the guidance of senior team members. This role focuses on building foundational skills across AI system development, model serving, inference pipelines, and enterprise integrations while developing familiarity with retrieval-augmented generation (RAG), orchestration patterns, and AI-assisted development tools. The position emphasizes learning established patterns, contributing to structured tasks, and growing toward independent delivery within a collaborative team environment.

Requirements

Bachelor's degree from an accredited institution in Computer Science, Machine Learning, Data Science, Software Engineering, Information Systems, Business Management, or a related discipline. Degrees in Artificial Intelligence or Machine Learning are welcomed and applicable.
A minimum of three (3) years of direct work experience in IT or a related discipline may be considered as a substitute for a degree.
Minimum of zero (0) to two (2) years of overall IT experience; recent graduates with relevant academic project experience or internships will be considered.
Foundational experience or academic exposure to system development, AI/ML concepts, or software engineering practices.
Foundational development experience in modern software engineering languages and environments; exposure to Python and common ML/AI libraries and frameworks preferred.
Exposure to or coursework in the full product development life cycle.
Basic SQL skills and foundational understanding of data concepts and structures.
Exposure to reporting tools and the ability to assist in developing and maintaining operational reports.
Foundational experience or coursework in application development using web frameworks, microservices, or equivalent technology.
Ability to communicate technical and business issues clearly to both technical and non-technical audiences with supervision.
Ability to manage assigned tasks and priorities with regular supervision and guidance.
Proficiency in MS Office applications including but not limited to Excel, Word, PowerPoint, and Outlook.
Must possess and maintain a valid driver's license and a driving record satisfactory to the company and its insurers (for travel).
Ability to work under supervision and collaboratively in a team environment; receptive to feedback, direction, and mentoring from senior team members.
Ability to manage assigned tasks and meet deadlines with guidance; 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, on technical and systems topics to both technical and non-technical audiences.
Ability to apply analytical and foundational technical understanding to assist in diagnosing problems and identifying practical solutions under direction.
Demonstrate strong attention to detail, reliability, and adherence to work schedules and policies.
Able to perform the essential functions of the position.

Nice To Haves

Application Developer certification(s) such as MCSD, OCP/M/E, CSD, or equivalent preferred.
AI/ML certifications or training from recognized vendors or community programs advantageous.
Academic or hands-on project experience with LLMs, generative AI, or ML model deployment.
Exposure to orchestration libraries or frameworks for building agentic or multi-step call flows.
Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud ML services.
Foundational exposure to security concepts for models and data including PII handling and data protection practices.
Exposure to vector databases or RAG concepts through coursework, personal projects, or early career experience.
Exposure to containerization concepts (Docker) or cloud-managed equivalents.
Foundational Python proficiency and exposure to machine learning libraries and toolkits; familiarity with LLM toolkits and ecosystems preferred.

Responsibilities

Support the implementation and maintenance of AI system components including model serving APIs, inference pipelines, and microservices under the direction of senior developers.
Assist in implementing integrations between LLMs, AI services, and enterprise applications including internal portals, chatbots, and workflow automation platforms.
Learn and apply retrieval-augmented generation (RAG) concepts including vector stores and knowledge indexes under the guidance of senior team members.
Assist in translating business requirements into technical specifications, flow diagrams, and implementation plans with supervision.
Leverage AI-assisted development tools to support Rapid Application Development (RAD) including generating code scaffolding, templates, unit-test stubs, and documentation under established guidelines and patterns.
Support data preparation activities in collaboration with Data & Analytics; assist in ensuring data quality, lineage, and appropriate transformations for AI-ready datasets.
Assist in packaging AI components using containerization (Docker) and support deployment automation activities (Kubernetes, serverless patterns) under direction.
Support CI/CD pipeline activities for model and service delivery; learn and apply model versioning and model registry practices (MLflow, model registry) under supervision.
Apply company AI governance guardrails under direction: data minimization, PII handling, prompt filtering, content moderation, and privacy and security best practices; support collaboration with Legal, Compliance, and Security as needed.
Write unit and integration tests for AI components and APIs under supervision; participate in release planning, deployment verification, and post-deployment monitoring; assist in troubleshooting production issues and documenting findings; maintain technical documentation, runbooks, and user guides as assigned; provide on-call support as required.
Keep current with LLM, generative AI, and MLOps best practices; learn and apply reusable patterns, templates, and components from the Center of Excellence knowledge base.
Work effectively across multi-disciplinary teams and present technical details to non-technical stakeholders.
Collaborate with a variety of people with tact, courtesy, and professionalism.
Maintain regular, dependable attendance and a high level of performance.
Maintain a high regard for personal safety, the safety of company assets and employees, and the general public.
Other daily, weekly, monthly, or special projects may be assigned.