B
Bounteousvia Lever
Full-Stack AI Engineer — AWS AI
Scottsdale, AZPosted 2d ago
ML EngineerMid LevelFull-time
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About the Role
Bounteous is a global AI Services firm where agentic engineering and human experience converge to deliver transformative business outcomes for the enterprise. We help organizations design, build, and scale AI-driven products, platforms, and processes. With more than 5,000 team members worldwide, Bounteous delivers AI that sticks, powering adoption and outcomes that move organizations from experimentation to true transformation. Bounteous is backed by New Mountain Capital, a New York-based growth-oriented investment firm that emphasizes business building.
Job Title: Full-Stack AI Engineer - AWS AI
Location: Scottsdale, Arizona (Onsite Preferred – 5days)
Employment Type: Contract
Domain: Retail
About the Role
We are seeking a highly motivated and technically strong Full-Stack AI Engineer - AWS AI to join our team. This individual will play a key role in designing, developing, deploying, and supporting enterprise-grade AI applications leveraging AWS AI services, Large Language Models (LLMs), agentic AI frameworks, APIs, cloud-native architectures, and modern web technologies.
The ideal candidate will possess strong full-stack engineering expertise combined with hands-on experience building production-ready AI solutions. This role will focus on accelerating enterprise AI adoption through scalable AI applications, intelligent automation, AI agents, workflow orchestration, and integration with internal and external enterprise systems.
The Engineer will collaborate closely with business stakeholders, data scientists, cloud architects, product teams, and AI governance teams to deliver secure, scalable, and impactful AI solutions.
Key Responsibilities
AI Application Development
Design, develop, and maintain AI-powered applications using AWS AI and Machine Learning services.
Build scalable enterprise solutions utilizing Generative AI, Retrieval-Augmented Generation (RAG), intelligent workflows, and AI agents.
Implement AI-enabled business solutions that enhance operational efficiency and customer experiences.
Collaborate with business teams to translate AI use cases into production-ready applications.
Full-Stack Engineering
Develop front-end and back-end components of AI-driven applications.
Build responsive user interfaces and APIs supporting AI-powered experiences.
Design reusable and scalable application architectures.
Develop secure, maintainable, and performant code following industry best practices.
Support integration of AI services into enterprise web applications and business platforms.
AWS AI & Cloud EngineeringAgentic AI SolutionsAPI & Enterprise Integrations
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management capabilities.
Ability to explain complex AI concepts to non-technical audiences.
Strong documentation and knowledge-sharing mindset.
Ability to work independently and in cross-functional teams.
Experience operating in agile development environments.
Required Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
Equivalent practical experience may be considered.
Experience
3-5 years of hands-on software engineering experience.
Experience building and deploying cloud-native applications.
Experience working on AI, machine learning, or Generative AI projects.
Experience supporting production enterprise applications.
Job Title: Full-Stack AI Engineer - AWS AI
Location: Scottsdale, Arizona (Onsite Preferred – 5days)
Employment Type: Contract
Domain: Retail
About the Role
We are seeking a highly motivated and technically strong Full-Stack AI Engineer - AWS AI to join our team. This individual will play a key role in designing, developing, deploying, and supporting enterprise-grade AI applications leveraging AWS AI services, Large Language Models (LLMs), agentic AI frameworks, APIs, cloud-native architectures, and modern web technologies.
The ideal candidate will possess strong full-stack engineering expertise combined with hands-on experience building production-ready AI solutions. This role will focus on accelerating enterprise AI adoption through scalable AI applications, intelligent automation, AI agents, workflow orchestration, and integration with internal and external enterprise systems.
The Engineer will collaborate closely with business stakeholders, data scientists, cloud architects, product teams, and AI governance teams to deliver secure, scalable, and impactful AI solutions.
Key Responsibilities
AI Application Development
Design, develop, and maintain AI-powered applications using AWS AI and Machine Learning services.
Build scalable enterprise solutions utilizing Generative AI, Retrieval-Augmented Generation (RAG), intelligent workflows, and AI agents.
Implement AI-enabled business solutions that enhance operational efficiency and customer experiences.
Collaborate with business teams to translate AI use cases into production-ready applications.
Full-Stack Engineering
Develop front-end and back-end components of AI-driven applications.
Build responsive user interfaces and APIs supporting AI-powered experiences.
Design reusable and scalable application architectures.
Develop secure, maintainable, and performant code following industry best practices.
Support integration of AI services into enterprise web applications and business platforms.
AWS AI & Cloud EngineeringAgentic AI SolutionsAPI & Enterprise Integrations
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management capabilities.
Ability to explain complex AI concepts to non-technical audiences.
Strong documentation and knowledge-sharing mindset.
Ability to work independently and in cross-functional teams.
Experience operating in agile development environments.
Required Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
Equivalent practical experience may be considered.
Experience
3-5 years of hands-on software engineering experience.
Experience building and deploying cloud-native applications.
Experience working on AI, machine learning, or Generative AI projects.
Experience supporting production enterprise applications.
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