Junior AI Solutions Engineer: LLMs & Enterprise Apps

Achieve; Tempe (AZ); On-site; USD 90,000 - 125,000; Full time

Benefits offered by this job

401(k) matching

Health, dental, and vision

Paid time off

Wellness programs

Pet care discounts

Care Fund

Diversity and inclusion ERGs

Job summary

Achieve is seeking an Associate AI Solutions Engineer to join our Technology team. You will support design, build, and deployment of AI-powered solutions across the organization, collaborating with senior engineers to deliver measurable outcomes for members and internal teams.

You will work with LLMs, RAG, and enterprise integrations, contributing to prompt libraries, MCP integrations, and reliable production systems while learning from experienced engineers and stakeholders.

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• 0–2 years software engineering experience with AI projects.
• Familiarity with LLMs, prompt engineering, RAG.
• Experience with APIs and cloud platforms (AWS/Azure/GCP).
• Strong communication and teamwork skills.

Responsibilities

• Design, build, and document AI solutions with cross-functional teams.
• Develop AI-powered applications, agents, and workflows.
• Implement LLM-based systems and MCP integrations.
• Integrate AI with enterprise systems (CRMs, data warehouses).
• Partner with stakeholders to deliver reliable, maintainable code.

Skills

AI apps

LLM techniques

APIs integration

Cloud platforms

Software fundamentals

Analytical skills

Communication

Collaboration

Education

Bachelor's degree

Tools

RAG

MCP

AI tooling

Prompt engineering

Job description

Achieve is seeking an Associate AI Solutions Engineer to join our Technology team. You will support design, build, and deployment of AI-powered solutions across the organization, collaborating with senior engineers to deliver measurable outcomes for members and internal teams.

You will work with LLMs, RAG, and enterprise integrations, contributing to prompt libraries, MCP integrations, and reliable production systems while learning from experienced engineers and stakeholders.