AI Engineer - Agentic AI Systems

• 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

Go Beyond “Model Usage”

• 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

AI Meets Hardware (Differentiator)

• 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

Build Platforms, Not Just Features

• Develop reusable components for:
• memory and context management
• tool integration
• knowledge retrieval
• Contribute to internal AI platforms used across teams

The pay range below is for Bay Area California only. Actual salary may vary based on a number of factors including job location, job-related knowledge, skills, experiences, trainings, etc. We also offer incentive opportunities that reward employees based on individual and company performance.

$133.2K - $192.8K USD

We use artificial intelligence to screen, assess, or select applicants for the position. Applicants must be eligible for any required U.S. export authorizations.

Background

• Master’s (or exceptional Bachelor’s) in CS, EE, or related field
• 3+ years experience (internships, research, or industry)

Technical Strength

• 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
• system design basics

Signal of Excellence (What Sets You Apart)

• 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

Bonus Points

• Experience with:
• LangChain, LlamaIndex, or similar
• vector databases (FAISS, Milvus, etc.)
• Exposure to:
• RAG, prompt engineering, or agent workflows
• hardware acceleration or performance optimization

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.