R&D Software Engineer

About the role

You will explore what comes next in the advanced development lab, prototyping technologies and approaches that product teams are not ready to bet on yet. R&D software engineers evaluate emerging frameworks, AI techniques, and architectural paradigms with honest, measured, data-driven assessments. You will have the freedom to experiment broadly across domains and the responsibility to produce genuinely transferable results: working prototypes, benchmark data, and clear-eyed recommendations about what is ready and what is not. Intellectual honesty is the core value here: killing a weak idea fast with good data is exactly as valuable as proving a strong one. You will also publish the benchmark reports that document what you evaluated and why it failed or succeeded, since the lab's credibility rests on rigorous, reproducible comparisons.

What you will achieve

• Build working prototypes of emerging technologies on aggressive timelines, demonstrating real capabilities honestly versus marketing claims
• Deliver candid technology evaluations with benchmarks, documented limitations, cost analysis, and clear readiness assessments for product teams
• Create transfer packages with working code, thorough documentation, and integration guides that product teams can adopt directly
• Prototype novel architectures spanning new AI approaches, distributed patterns, or developer tools, validated with measured, reproducible results
• Kill weak concepts decisively with well-designed experiments and clear write-ups, focusing investment and attention on genuine opportunities

What you will bring

Must-haves

• 4 to 7 years of software engineering with demonstrated ability to prototype quickly across unfamiliar technical domains
• Strong computer science fundamentals enabling fast learning: productive in a new stack, language, or paradigm within weeks
• Comfort with deep ambiguity: incomplete documentation, shifting goals, and open-ended problem spaces without clear right answers
• Excellent technical writing for research notes, evaluation reports, and transfer documentation that other engineers can act on
• Self-direction: defining your own milestones, experiments, and success criteria within unstructured research environments
• Intellectual honesty: reporting negative results clearly and changing your position when the data demands it
• BS in Computer Science; MS preferred for research-oriented roles

Nice-to-haves

• Patent filings or publications in software, AI, or distributed systems with recognized contributions
• Experience with academic or industry research lab collaborations and joint programs
• Familiarity with grant-funded research structures, milestones, and technical reporting requirements
• Breadth across multiple paradigms: systems programming, ML, web, mobile, or embedded