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Ai Applications Engineer Jobs (NOW HIRING)

Applications Engineer

Poway, CA ยท On-site

$150K - $180K/yr

As EPC Power expands aggressively into hyperscale and AI-driven data center markets, we focus on ... The Applications Engineer is a customer-facing technical expert supporting EPC Power's growth ...

Applications Engineer

Shoreview, MN ยท On-site

$130K - $160K/yr

Principal Applications Engineer Ready to architect and deliver next-generation intelligent motion ... AI-enabled diagnostics, and next-generation industrial software platforms that improve system ...

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Ai Applications Engineer information

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$50.5K

$110.7K

$152K

How much do ai applications engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for ai applications engineer in the United States is $110,698.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $135,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Applications Engineer, and why are they important?

To thrive as an AI Applications Engineer, you need strong programming abilities (Python, Java, or C++), a solid understanding of machine learning algorithms, and a relevant degree in computer science or engineering. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms, and data processing tools is typically required, along with certifications in machine learning or AI. Excellent problem-solving, collaboration, and communication skills help you translate business needs into effective AI solutions and work efficiently with cross-functional teams. These skills are critical for building scalable, reliable AI systems that deliver tangible value to organizations.

How does an AI Applications Engineer typically collaborate with data scientists and software developers on project teams?

As an AI Applications Engineer, you will often serve as a bridge between data scientists, who build and optimize machine learning models, and software developers, who integrate these models into production systems. Collaboration usually involves translating model requirements into scalable application features, ensuring model outputs align with user needs, and troubleshooting technical challenges that arise during deployment. Regular meetings, code reviews, and shared documentation are common practices to keep everyone aligned and ensure seamless integration. This cross-functional teamwork enhances both the technical robustness and usability of AI-powered applications.

What are AI Applications Engineers?

AI Applications Engineers are professionals who design, develop, and integrate artificial intelligence (AI) solutions into software applications to solve real-world problems. They work closely with data scientists, software engineers, and business stakeholders to build and deploy machine learning models, automate processes, and enhance user experiences. Their responsibilities often include selecting appropriate AI technologies, writing code, testing models, and optimizing performance. AI Applications Engineers play a key role in translating AI research and prototypes into scalable and maintainable products used in industries like healthcare, finance, retail, and more.

What is the difference between Ai Applications Engineer vs Data Scientist?

AspectAi Applications EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teamsAnalyzes data, builds models, interprets results
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech, research institutions

While both roles involve AI and data, Ai Applications Engineers focus on developing and deploying AI solutions in engineering contexts, whereas Data Scientists analyze data to extract insights. The roles often overlap but differ mainly in their primary focus and application environment.

More about Ai Applications Engineer jobs
What cities are hiring for Ai Applications Engineer jobs? Cities with the most Ai Applications Engineer job openings:
What states have the most Ai Applications Engineer jobs? States with the most job openings for Ai Applications Engineer jobs include:
Infographic showing various Ai Applications Engineer job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 90% Full Time, 4% Part Time, and 5% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution, with an average salary of $110,698 per year, or $53.2 per hour.
Senior Software Engineer AI Applications

Senior Software Engineer AI Applications

Bezos Academy

Phoenix, AZ โ€ข On-site

$157K - $298K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Senior Software Engineer AI Applications

At Bezos Academy, we believe all children deserve the great start that excellent early education provides, including in under-resourced communities. Our mission is to nurture the potential in every child to become a creative leader, original thinker, and lifelong learner by inventing the solutions needed to scale early childhood education. We operate a multi-state network of schools in under-resourced communities, offering quality Montessori-inspired preschool at no cost to families. We also create tools, products, technology, and other solutions designed to reach young children and their caregivers well beyond the walls of our schools. We aspire to have a profound, large-scale impact on children ages zero to five. At Bezos Academy, we are committed to expanding access to play-focused preschool education in underserved communities, aiming to improve long-term educational, social, and developmental outcomes in ways that create meaningful and lasting impact.

As a Senior AI Applications Engineer at Bezos Academy, you will help build AI-powered software applications that support teachers' abilities to deliver measurable results in early childhood education. As a hands-on, results-driven software developer, you will play a pivotal role in developing intelligent systems for teachers, staff, and families with a small product development team. Your products will both thrill and delight their users and enable our national school network to nurture young children's originality, foster self-agency, cultivate a love for learning, and spark joy.

You have a proven track record of combining machine-learning models, high-quality data, and human-centered workflows into production-ready tools; you consistently deliver solutions that solve human problems. Resourceful throughout the software-development lifecyclefrom research and prototyping to deployment, monitoring, and evaluationyou work effectively despite constraints on time and resources. In past roles, you have successfully launched AI-powered applications in collaboration with product-development teams. As a software engineer with a customer mindset, you take pride in applying practical AI workflows and sound software-engineering principles to build high-impact AI products. Adept at working from scratch, you navigate ambiguity, iterate quickly, and shape solutions that earn customer love. Hands-on experience with evaluations, inference validation, and AI guardrails has helped you strengthen the safety, performance, and ethics of AI features. You recognize exceptional work when you see it and instill that same passion in others.

In this role, you will focus on building, measuring, and iterating for children. Motivated equally by great products and great impact, you are deeply inspired by our mission to expand access to quality early childhood education and experiences.

Location: Washington, Arizona, Florida, Kentucky, or Texas, within two hours' drive to multiple Bezos Academy preschools (please see our website for school locations); Seattle, WA preferred. Relocation support is available for those willing to relocate to Seattle, WA.

Compensation and Benefits: This is a full-time, benefits-eligible, salaried position. The full salary range for this position, across applicable United States geographies, is $157,000 - $298,000 per year. The upper portion of the salary range is typically reserved for employees who have been in the role for multiple years and have demonstrated strong performance over time. Starting salary will vary by location, qualifications, and prior experience. This role includes 15 paid days of vacation, 4 days of paid personal time off, 9 paid days of sick (care) time, 9 paid holidays, 5 paid days off for an organization-wide winter break, and additional time off if required by applicable law. Benefits for this role include medical, dental, and vision insurance, life insurance, disability insurance, a 401(k) plan with a 4% employer contribution match, paid parental leave, an employer-matched flexible spending account for dependent care, and more. Please see here for details.

Minimum Qualifications: Bachelor's degree or equivalent experience; Eight or more years of experience developing and deploying full-stack applications, including two or more years working on AI-powered applications in production environments; Proficiency in Python for backend development and integrating AI capabilities; Working knowledge of TypeScript and SQL for full-stack development and data handling; Experience integrating pre-trained foundation models, including large language models (LLMs) and multi-modal models, into production applications; Familiarity with model evaluation techniques, such as prompt testing, output validation, and performance monitoring; Experience with AWS services, especially those relevant to AI applications (e.g., Bedrock, Lambda, EC2, S3, RDS, DynamoDB); Understanding of AI safety practices, including inference validation, implementing guardrails, and handling personally identifiable information (PII) and sensitive data responsibly; Ability to speak, read, and write English fluently.

Preferred Qualifications: Experience with LangChain or similar frameworks for orchestrating LLM workflows and agentic behavior (e.g., tool use, planning, memory); Familiarity with AWS AgentCore; Exposure to vector databases and embedding techniques, especially in retrieval-augmented generation (RAG) workflows; Experience implementing AWS Bedrock Guardrails or similar safety mechanisms; Understanding of LLM evaluation strategies, including prompt engineering and human feedback loops; Experience with DevOps practices, including CI/CD pipelines, test automation, and infrastructure-as-code tools (e.g., AWS CDK).