Applied AI Engineer

About the Role

The Applied AI Engineer I supports, maintains, and enhances ESRT’s portfolio of AI-enabled enterprise applications. This early-career role offers recent graduates hands-on experience with large language models, retrieval-augmented generation (RAG), AI agents, and intelligent automation, and helps them develop software engineering skills for production applications. The role works closely with senior engineers and technical leadership to learn the application portfolio and codebase and complete well-defined tasks. Regular mentorship and code review support skill development and greater responsibility over time.

Key Responsibilities

• Support software design, development, tests, and deployment under senior guidance, and help build applications that incorporate large language models and other AI capabilities.
• Support retrieval-augmented generation (RAG) workflows, such as document ingestion, chunking, embeddings, indexing, and retrieval.
• Help develop AI agents, agent tools, and tool-calling workflows, and convert approved prototypes into production-ready features under senior guidance.
• Implement small, well-defined features and components under close guidance, with code review by senior engineers.
• Learn the architecture and codebase of AI applications, such as model integrations, RAG pipelines, agent workflows, evaluation systems, and observability.
• Write unit and integration tests and help develop automated tests and application monitoring.
• Learn and apply safeguards for data privacy, access control, and responsible AI practices.
• Help build APIs, backend services, and data processing workflows that connect AI solutions with internal systems, with support for data ingestion and ETL processes.
• Write clean, well-documented code, use Git for version control, participate in peer code reviews, and follow the team’s CI/CD practices.
• Maintain technical documentation, communicate progress and blockers clearly, and collaborate with internal teams, vendors, and business stakeholders in an agile environment.

Requirements & Tech Stack

• Solid foundation in Python; exposure to at least one additional language (e.g., C#, Java, TypeScript) through coursework or projects.
• Exposure to large language models, APIs, or other AI services through coursework, internships, or personal projects.
• Basic knowledge of software engineering fundamentals: version control (Git), tests, and code review.
• Familiarity with API development or use, databases, and data models.
• Willingness to learn about AI application risks, such as prompt injection and sensitive-data exposure, and responsible AI practices.
• Strong problem resolution skills, ability to learn new tools and technologies quickly, and clear written and verbal communication.
• Ability to collaborate, take direction from senior engineers, and show initiative on assigned tasks.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field (recent graduates welcome), or equivalent hands-on experience through internships, bootcamps, or personal/academic projects.
• Coursework or project exposure to RAG concepts (embeddings, vector search), Azure OpenAI or comparable AI platforms, cloud platforms (Azure, AWS, or GCP), or traditional machine learning.

Compensation

• $135,000 - $145,000 a year
• Competitive base salary and bonus
• Discretionary annual bonuses