Senior Software Engineer, AI Team (Oakland, CA)

 

Senior Software Engineer – AI Innovation

Location: Oakland, CA (Onsite – HQ)
Team: Artificial Intelligence
Reports to: Director of Engineering, AI
Type: Full-Time

 

Overview

Fictiv is reimagining how manufacturing works in an AI-first world.

Our AI Innovation Team operates like an internal startup—focused on discovering, validating, and scaling entirely new product capabilities across both Fictiv and Misumi. This isn’t about incremental improvements or maintaining existing systems. It’s about identifying what should exist next and building it from the ground up.

As a Senior Software Engineer on this team, you’ll work on early-stage ideas, rapidly turning concepts into functional prototypes, testing them with real users, and evolving the strongest signals into production systems.

If you’re energized by ambiguity, driven by impact, and motivated by building things that don’t yet exist, this role is designed for you.

What You’ll Work On

• Discover and define high-leverage AI opportunities across manufacturing and supply chain workflows
• Build rapid prototypes using real-world company data to test new product ideas
• Develop and iterate on LLM-powered systems, focusing on usability, reliability, and impact
• Collaborate directly with customers and internal stakeholders to validate real-world use cases
• Transform validated concepts into scalable, production-ready systems with engineering partners
• Explore emerging AI models, tools, and frameworks to push the boundaries of what’s possible
• Capture learnings, system designs, and experiment results to support long-term scaling
• Contribute to shaping the AI roadmap across Fictiv and Misumi

What You Bring

• 8+ years of software engineering experience
• Strong experience building and shipping LLM-based applications used in production
• Proficiency in modern development environments (TypeScript/JavaScript and AWS preferred)
• Hands-on experience with:
• Prompt design and iteration
• LLM evaluation and testing methodologies
• Guardrails, reliability patterns, and system design for AI applications
• A track record of designing experiments and using data to validate technical decisions
• Authorization to work in the U.S. without current or future sponsorship

Nice to Have

• Experience building AI-first products end-to-end
• Comfort working across multiple languages, tools, and architectures
• Experience with large, unstructured, or messy datasets
• Background in applied machine learning or AI systems

How You’ll Succeed

• You think like a builder and an owner, not just an implementer
• You’re motivated by solving real business problems—not just writing code
• You move quickly, test ideas early, and learn from real-world feedback
• You’re comfortable op