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Generative Ai Associate Jobs in Boise, ID (NOW HIRING)

Generative Ai Associate information

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How much do generative ai associate jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for generative ai associate in Boise, ID is $16.58, according to ZipRecruiter salary data. Most workers in this role earn between $15.10 and $17.60 per hour, depending on experience, location, and employer.

What is a generative AI associate?

Generative AI Associates are professionals who support the development, implementation, and management of AI systems that create new content such as text, images, audio, or code. They often work with machine learning models, particularly those based on generative techniques like large language models or diffusion models. Their responsibilities may include data preparation, model training, prompt engineering, and evaluating AI outputs. Generative AI Associates typically collaborate with data scientists, engineers, and product teams to ensure AI solutions meet business and ethical standards.

How does a generative AI associate typically collaborate with data scientists and engineers on projects?

As a Generative AI Associate, you will often work closely with data scientists to understand data requirements and model objectives, and with engineers to help deploy and integrate AI solutions into existing systems. Collaboration usually involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical issues together. You may also assist with data preprocessing, building prototypes, and documenting workflows to ensure smooth handoffs between teams. This cross-functional teamwork is essential for delivering robust and scalable generative AI applications.

What are the key skills and qualifications needed to thrive as a generative AI associate, and why are they important?

To thrive as a Generative AI Associate, strong foundations in machine learning, data analysis, and programming (often Python) are essential, typically supported by a degree in computer science or a related field. Familiarity with popular AI frameworks such as TensorFlow, PyTorch, and experience using cloud platforms like AWS or Azure are commonly required, along with knowledge of prompt engineering and large language models. Creative problem-solving, effective communication, and a collaborative mindset are standout soft skills in this role. These skills and qualities enable associates to design innovative AI solutions, communicate complex ideas, and work efficiently in fast-evolving, interdisciplinary environments.

What are the most commonly searched types of Generative Ai jobs in Boise, ID?

The most popular types of Generative Ai jobs in Boise, ID are:

What are popular job titles related to Generative Ai Associate jobs in Boise, ID?

For Generative Ai Associate jobs in Boise, ID, the most frequently searched job titles are:

What job categories do people searching Generative Ai Associate jobs in Boise, ID look for?

The top searched job categories for Generative Ai Associate jobs in Boise, ID are:

Infographic showing various Generative Ai Associate job openings in Boise, ID as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $34,491 per year, or $16.6 per hour.

AI Technical Lead

Meridian, ID • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 23 days ago


Job description

Our AI Technical Lead is responsible for designing and delivering scalable AI systems that enable intelligent applications across the organization. This role combines hands-on engineering, system architecture, and technical leadership to build production-grade machine learning and generative AI platforms. The Lead works closely with product, data engineering, and infrastructure teams to bring AI capabilities from experimentation into reliable production systems while supporting the organization's broader AI strategy and innovation initiatives.
Location: this position has preference to based in hybrid work location (onsite and WFH). There may be opportunity for fully remote within a mutually acceptable location. #LI-Hybrid
Success Looks Like:
  • AI systems move efficiently from experimentation and pilot phases into reliable production environments.
  • Engineering teams operate within clear architectural standards and scalable development practices.
  • AI capabilities deliver measurable business impact.
  • The organization is able to rapidly develop, test, and scale new AI-driven solutions

Key Responsibilities:
Technical Leadership
  • Provide technical leadership and mentorship to a team of AI engineers.
  • Establish engineering standards, coding practices, and architectural guidelines for AI system development.
  • Lead design reviews, guide technical decision making, and resolve complex engineering challenges.
  • Serve as a technical escalation point for AI system architecture and implementation

AI System Architecture
  • Architect end-to-end AI systems including data pipelines, model training workflows, AI service layers, and scalable AI application infrastructure.
  • Design and implement AI-powered applications including large language model (LLM) systems and retrieval-based knowledge applications.
  • Define architecture patterns that support experimentation, rapid prototyping, and production deployment of AI capabilities.
  • Develop service-based architectures that enable AI functionality to be integrated across enterprise applications.

AI Engineering & Development
  • Develop and deploy machine learning and generative AI solutions that support enterprise use cases.
  • Build reusable AI services and platform components that enable teams to rapidly develop and scale AI capabilities.
  • Implement evaluation, monitoring, and reliability systems to ensure consistent model performance.
  • Optimize AI pipelines for performance, scalability, and operational efficiency.

Cloud & MLOps
  • Design cloud-native infrastructure supporting AI and machine learning workloads.
  • Implement containerized AI services and automated deployment pipelines.
  • Support the development of scalable AI platforms that enable experimentation, model deployment, and operational monitoring.
  • Ensure AI systems follow best practices for reliability, observability, and cost management.

Collaboration & Delivery
  • Work closely with product managers, data engineers, and business stakeholders to identify and deliver high-value AI use cases.
  • Translate business requirements into scalable AI architecture and engineering solutions.
  • Partner with cross-functional teams to move AI solutions from pilots and experimentation into production environments.
  • Support initiatives that enable the organization to scale AI capabilities across multiple business domains.

Responsible AI & Governance
  • Promote responsible AI practices including transparency, fairness, and privacy considerations.
  • Implement safeguards and monitoring systems for AI applications operating in production.
  • Collaborate with security and compliance teams to ensure AI systems meet regulatory and organizational standards.

Required Education (must meet one of the following):
  • Bachelor or International Equivalency degree in Cybersecurity, Computer Science, Electrical Engineering, Information Systems, or closely related field of study; or equivalent work experience (Two years' relevant work experience is equivalent to one-year college)
  • Associate Degree in Computer Science, Electrical Engineering, Information Systems, or closely related field of study + 2 years additional experience

Required Experience: 6/+ years of experience in software engineering, machine learning engineering, and/or related AI/ML technical roles. Experience should include:
  • Experience designing and deploying machine learning or generative AI systems.
  • Strong programming experience in Python and modern backend technologies.
  • Experience building distributed systems or cloud-native architectures.
  • Experience implementing machine learning workflows or model deployment pipelines.

Preference for additional experience in:
  • Developing large language model (LLM) applications.
  • Experience with retrieval-based AI systems or knowledge-driven applications.
  • Working with cloud platforms and modern DevOps practices.
  • Mentoring engineers, leading technical initiatives, and/or serving as a technical lead
  • Working with large-scale data pipelines

As of the date of this posting, a good faith estimate of the current pay range is $118,506 - $177,758. The position is eligible for an annual incentive bonus (variable depending on company and employee performance). The pay range for this position takes into account a wide range of factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, travel requirements, internal equity, business or organizational needs, and alignment with market data. At Blue Cross of Idaho, it is not typical for an individual to be hired at or near the top range for the position. Compensation decisions are dependent on factors and circumstances at the time of offer.
We offer a robust package of benefits including paid time off, paid holidays, community service and self-care days, medical/dental/vision/pharmacy insurance, 401(k) matching and non-contributory plan, life insurance, short and long term disability, education reimbursement, employee assistance plan (EAP), adoption assistance program and paid family leave program.
We will adhere to all relevant state and local laws concerning employee leave benefits, in line with our plans and policies.
Reasonable accommodations
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.