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Internship Tech Stack Jobs (NOW HIRING)

Twitch

Software Engineer, Safety

San Francisco, CA · On-site

Responsibilities : • Learn about and make contributions to our tech stack, back and front end, ... internship, school or solo projects. • Working knowledge of modern programming languages and ...

Fitch Group

Software Engineer, Full Stack

Manhattan, NY · On-site

$88K - $105K/yr

Our technology stack is modern - cloud based, containerized, serverless and microservices oriented ... What You Need to Have: * 1+ years of professional Java experience (internships, or strong personal ...

Fitch Solutions

Software Engineer, Full Stack

Manhattan, NY · On-site +1

$88K - $105K/yr

Our technology stack is modern - cloud based, containerized, serverless and microservices oriented ... What You Need to Have: * 1+ years of professional Java experience (internships, or strong personal ...

Fitch Group

Software Engineer, Full Stack

Manhattan, NY · On-site +1

$88K - $105K/yr

Our technology stack is modern - cloud based, containerized, serverless and microservices oriented ... What You Need to Have: * 1+ years of professional Java experience (internships, or strong personal ...

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Internship Tech Stack information

What is the difference between Internship Tech Stack vs Junior Software Developer?

AspectInternship Tech StackJunior Software Developer
Required CredentialsBasic coding skills, coursework, or certificationsBachelor's degree in CS or related field, some certifications
Work EnvironmentInternship programs, entry-level projects, mentorshipFull-time employment, collaborative teams, project ownership
Industry UsageInternship programs across tech companies, startups, and corporationsEntry-level roles in software development teams
Common Search/ComparisonYesYes

The main difference between Internship Tech Stack and Junior Software Developer lies in experience level and responsibilities. Internships focus on learning, mentorship, and gaining foundational skills, while Junior Software Developers handle more complex tasks and contribute to ongoing projects. Both roles are essential for career growth in tech, with internships serving as a stepping stone to full-time developer positions.

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Internship Tech Stack jobs near you
Infographic showing various Internship Tech Stack job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution.
DATA501: Data Intelligence Stack Owner

DATA501: Data Intelligence Stack Owner

JerseySTEM, Inc.

Remote

Other

This job post has expired today. Applications are no longer accepted.

Job description

About JerseySTEM
All JerseySTEM roles are pro-bono (unpaid) positions.
JerseySTEM is a mission-driven professional network of pro-bono contributors dedicated to improving access to STEM education and career pathways for underserved middle school girls in New Jersey.
Members contribute their professional skills and leverage their networks in service of the organization's gender-equity agenda.
Membership is a minimum six-month commitment of approximately six flexible hours per week and includes a $100 refundable deposit, returned after six months of active membership. K-12 educators, retirees, veterans, interns, and students are exempt from the deposit.
Overview
This is a pro-bono volunteer position.
JerseySTEM is seeking an AI-Forward Data Intelligence Stack Owner to lead the evolution of our data-to-intelligence pipeline. The scope of this role is strictly focused on the Intelligence Layer of the tech stack, transforming organizational data into automated insights
You will architect a stack that leverages Generative AI, Automated Data Pipelines, and Predictive Modeling to provide real-time, actionable intelligence. You are the bridge between raw data silos and an AI-enhanced decision-making culture.
Responsibilities
  • AI-Centric Architecture: Design and oversee a data stack (Google BigQuery, Vertex AI, or similar) that prioritizes AI readiness and automated data flow.
  • Generative Insights: Implement AI "Chat-with-your-Data" interfaces and LLM-driven summarization for stakeholders to interact with organizational data.
  • Predictive Analytics: Move beyond historical reporting to build models that predict volunteer churn, student engagement trends, and fundraising opportunities.
  • Automated Governance: Utilize AI tools to monitor data quality, flag anomalies, and ensure privacy compliance automatically.
  • Orchestration: Integrate data from platforms (Salesforce, Jira, Google Workspace) using AI-friendly ETL/ELT processes that minimize manual intervention.
  • Implementation: Directly configure and code/test the initial data pipelines, AI integrations, and reporting logic before scaling through the lean team."
  • Team Leadership: Recruit and mentor a "Lean Data Team" focused on modern techniques like prompt engineering for data, automated visualization, and data engineering.

Qualifications
  • Applied AI for Analytics: Strong understanding of how to use LLMs specifically for data extraction, SQL generation, and automated synthesis
  • Modern Data Stack Expertise: Experience with cloud data warehouses and AI-integrated BI tools (e.g., Looker's Duet AI, Power BI Copilot).
  • Data Engineering Mindset: Proficiency in SQL and Python, with an emphasis on building clean data for AI consumption.
  • Visionary Thinking: Ability to replace spreadsheets with automated, intelligent solutions
  • Ability to translate AI-driven outputs simply to cross-functional partners.
  • Comfortable working in a remote, distributed, member-driven environment.
  • Minimum commitment of 6 hours per week.
Preferred Qualifications
  • Experience building data products, automated reporting agents.
  • Previous experience in a leadership role within a tech-focused nonprofit or startup leading through shifts from legacy to automated data ecosystems.
  • Familiarity with "AI-as-a-Service" platforms and low-code AI automation.
  • Retired professionals or those seeking meaningful pro bono work are welcome.
Key Outcomes
  • The Intelligent Stack: A data environment where AI performs the first-layer of analysis.
  • Self-Service Intelligence: Stakeholders can get answers to complex questions through automated agents rather than waiting for manual reports.
  • Zero-Latency Insights: Implementing systems where key stakeholders receive automated proactive alerts and summaries via Chat/Email driven by data anomalies or trends
  • Scalable Team: A high-performing member team trained in AI-forward data practices

Apply