Software Engineering Intern, Applied AI

Envita Solutions • Indianapolis, IN

7d • $18 - $21 • Onsite

About The Position

Envita Solutions, formerly known as Heritage Interactive Services, is a leading total waste management partner dedicated to fostering a healthier planet by transforming complex waste challenges into sustainable solutions. Headquartered in Indianapolis, Indiana, Envita Solutions operates in the U.S., Mexico, and Canada, has over 300 employees, and a network of over 3,000 supplier partners. A division of The Heritage Group, Envita Solutions is part of a portfolio of more than 30 companies specializing in heavy construction and materials, environmental services, and specialty chemicals. With unique access to research and development and a leading hard tech corporate venture capital portfolio, Envita Solutions is at the forefront of waste and climate challenge innovation.
At Envita, our guiding principles are the foundation of our company. Our vision is to foster a healthier planet by transforming complex waste challenges into sustainable solutions. We exist to protect human health and the environment and build a safer, more sustainable world. We believe in creating enduring value, building long-term relationships and mutual trust, betting on our people, keeping our eyes open for opportunity, tackling the big problems, and doing the right thing-always.
We are seeking a Software Engineering Intern to join Envita's Digital Innovation team for the summer. Our team builds and operates AI-powered applications for document processing, knowledge retrieval, and workflow automation that support Envita's operations and sustainability mission. This role is software engineering first: the intern will strengthen the foundations those applications depend on, including data quality, logging and observability, integrations, and test coverage, while gaining hands-on exposure to how LLM- and agent-based systems are built and run in production. This is a great fit for a student who enjoys making systems more reliable, readable, and maintainable and wants to understand how modern AI applications work under the hood.

Requirements

• Academic, internship, or project-based experience writing Python for real applications (scripts, services, data pipelines, or tools) beyond coursework exercises.
• Experience consuming or building REST APIs and/or webhook-based integrations.
• Familiarity with Git-based workflows (branching, pull requests, code review) through coursework, internships, or personal/open-source projects.
• Proficiency in Python, including writing clean, testable, well-structured code.
• Working knowledge of SQL and comfort working with messy, real-world data.
• Understanding of software engineering fundamentals: testing, debugging, logging, error handling, and version control.
• Foundational understanding of how LLM-based applications are built (prompting, retrieval, structured output, tool and agent orchestration) and interest in going deeper.
• Strong problem-solving skills and the persistence to work carefully through ambiguous, detail-heavy problems.
• Effective communicator, able to document work and explain technical decisions to technical and non-technical audiences.

Nice To Haves

• Exposure to LLM tooling preferred: prompt engineering, LLM APIs, agent frameworks (e.g., LangGraph, Claude Code, or similar), or RAG / vector search / embeddings.
• Coursework or project experience in machine learning, databases, or data engineering is a plus.
• Familiarity with cloud platforms (Azure preferred) and containerized deployments is a plus.

Responsibilities

• Ensures Health & Safety is the number one goal by following policies, processes, and always acting in a safe manner.
• Data Quality & Cleanup: Profile, clean, deduplicate, and normalize the structured and unstructured datasets that feed our AI applications; write repeatable scripts and validation checks so improvements persist.
• Logging & Observability: Improve logging, error handling, and monitoring across Python and C# services and data pipelines so issues are easier to diagnose and system behavior is measurable.
• Integration Development: Build and harden integrations using REST APIs, webhooks, and scripting to connect internal systems, data sources, and AI services.
• Code Quality & Technical Debt: Refactor existing code, add automated tests, improve documentation, and work through backlog items that keep our AI systems maintainable.
• AI Application Support: Contribute to LLM-based features such as structured data extraction from documents, retrieval (RAG / vector search), and agent workflows, including building evaluation and test harnesses for them.
• Prototyping: Deliver small, well-scoped proof-of-concept tools or automations that demonstrate measurable value.
• Cross-Team Collaboration: Partner with technology and business teams to understand how data and systems are used and where improvements will have the most impact.
• Engineering Practices: Work within the team's standard development workflow, including version control (Git/GitHub), code review, issue tracking, and CI, and communicate progress clearly.
• Additional duties and responsibilities as assigned, including but not limited to continuously growing in alignment with the Company’s core values, competencies, and skills.

Benefits

• paid experiences
• network with other students and professionals
• gain useful skills
• receive mentoring
• make their own contributions to the organization
• weekly hosted events focused on professional development, team building, and community service

What This Job Offers

• Career Level: Intern