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Outcom.ai

Software Engineering Intern (6 Months)

Posted 7 Days Ago
Remote or Hybrid
Hiring Remotely in United States
Internship
Remote or Hybrid
Hiring Remotely in United States
Internship
Six-month engineering internship building production backend services and AI pipelines. Design SQL schemas (PostgreSQL), implement SaaS integrations (REST APIs, webhooks), work with embeddings, transformer models and vector databases, build end-to-end data processing pipelines, and contribute to code reviews and architecture discussions.
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About the Role

We’re hiring engineering interns who can think clearly, solve hard problems, and build real systems. You’ll work across backend engineering, AI pipelines, vector search, and integrations – contributing to production features from day one.

What You’ll Do
  • Build backend services in Java, Node.js, or Python

  • Design schemas and work with SQL databases (PostgreSQL)

  • Implement integrations with external SaaS systems (REST APIs, webhooks)

  • Work with embeddings, transformer-based models, and vector databases

  • Build and debug data processing pipelines end-to-end

  • Contribute to technical discussions, code reviews, and architecture decisions

What You Need
  • Proficiency in one of: Java, Node.js, or Python

  • Strong foundation in data structures, algorithms, and core CS concepts

  • Understanding of SQL and basic schema design

  • Clear reasoning and problem-solving ability

  • Ability to learn new technologies quickly and operate with ownership

Nice to Have
  • Exposure to transformer models or embedding workflows

  • Experience with vector DBs (Weaviate, Pinecone, Qdrant, Milvus)

  • Familiarity with building or consuming SaaS integrations

  • Knowledge of Docker, Git, or basic cloud concepts

  • Prior projects in backend systems, ML/AI, or distributed systems

What You’ll Gain
  • Hands-on experience building production-grade backend + AI systems

  • Deep exposure to embeddings, retrieval, and integrations

  • Strong engineering mentorship

  • Opportunity for full-time conversion based on performance

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