AI Software Development Engineer - Intern

AlteraSan Jose, CA
$48 - $52Onsite

About The Position

AI is shifting from models to autonomous systems. At Altera, we are building agentic AI platforms tightly coupled with FPGA acceleration, enabling intelligent systems that can reason, act, and scale in real-world environments. This role is designed for high-potential engineers early in their careers who want to work on cutting-edge AI (LLMs + agents + RAG), gain exposure to hardware-software co-design, and grow quickly into technical leaders in AI systems.

Requirements

  • Currently pursuing a Master’s or PhD in CS, EE, or related field
  • Strong coding skills in Python (C++ is a plus)
  • Hands-on experience building AI/ML projects, OR backend / distributed systems
  • Solid fundamentals in data structures
  • Solid fundamentals in system design basics

Nice To Haves

  • Experience with LangChain, LlamaIndex, or similar
  • Experience with vector databases (FAISS, Milvus, etc.)
  • Exposure to RAG, prompt engineering, or agent workflows
  • Exposure to hardware acceleration or performance optimization
  • You’ve built something non-trivial: AI project, open-source contribution, or research prototype
  • You learn new frameworks quickly and ship working systems
  • You’re curious about how systems work end-to-end, not just models

Responsibilities

  • Develop LLM-powered agents that use tools, APIs, and data to complete complex tasks
  • Implement RAG pipelines for large-scale knowledge integration
  • Ship end-to-end systems from data ingestion → reasoning → action
  • Design multi-step reasoning workflows, not just prompt calls
  • Evaluate and improve model behavior (accuracy, latency, cost)
  • Work with both open-source and frontier models
  • Collaborate with FPGA/ASIC teams on hardware-aware AI design
  • Learn how AI systems are optimized across CPU / GPU / FPGA
  • Explore efficient inference and system-level performance tradeoffs
  • Develop reusable components for memory and context management, tool integration, and knowledge retrieval
  • Contribute to internal AI platforms used across teams

Benefits

  • Incentive opportunities that reward employees based on individual and company performance.
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