Instrumental Logo

Instrumental

Sr. Software Engineer - Backend/Full-stack

Reposted 11 Days Ago
Be an Early Applicant
Hybrid
Palo Alto, CA, USA
185K-225K Annually
Senior level
Hybrid
Palo Alto, CA, USA
185K-225K Annually
Senior level
The Senior Platform Engineer will own the software development lifecycle, improve platform performance, and ensure alignment with engineering needs, particularly in AI tools and data processing.
The summary above was generated by AI
Instrumental builds the manufacturing acceleration platform behind the world's most complex electronics. We capture digital exhaust and engineering context from assembly lines — images, test logs, BOM data, performance, repair cycles — and our AI engines identify insights that are difficult or impossible for human engineers to find. We accelerate the companies building the AI era by improving manufacturing yield, throughput, and ramp. NVIDIA, Meta, L3Harris, and their manufacturing partners rely on Instrumental to accelerate new product introduction and production.

We're entering one of the most important periods in our company's history. Over the next year, we'll be rebuilding our platform layer for a scale it wasn't originally built for — and the engineer who joins now will shape that architecture as much as anyone.

We're looking for a Backend/Platform engineer who owns hard, ambiguous systems problems end-to-end, and who does it in a way that makes the rest of engineering want to build on what you ship. This isn't a role where you inherit an architecture and maintain it. You'll partner directly with engineering leadership and teams across product, AI, and edge systems — not just to keep the platform running, but to raise the bar on how we build.

What You'll Be Doing:
  • Own the systems that matter most. Take full lifecycle ownership of core platform services — design, build, deploy, operate — especially the ones where the obvious architecture doesn't hold up, and you have to design a better one.
  • Make the rest of engineering better at shipping. You'll push back when a design won't scale, an approach trades short-term speed for long-term pain, or a "good enough" isn't. You earn the standing to do this by being right, consistently, and by being someone teams want in the room.
  • Move fast without creating friction. You'll make architectural calls, iterate in real time, and adjust course mid-build — all while keeping other teams, and the systems they depend on, aligned and stable. No surprises, no silent breakage.
  • Build the platform as you go. Better tooling, smarter use of AI-assisted development, sharper observability and incident response — you'll leave the platform meaningfully stronger than you found it, and you'll do it in a way that earns trust rather than working around people.

This role probably isn't the right fit if...
  • You want a well-defined system to maintain, rather than one to build and rebuild as the business scales.
  • When something breaks or doesn't scale, you wait for direction instead of diagnosing and fixing it yourself.
  • You've mostly worked in codebases where the hard architectural decisions were already made — this job is proactive, not maintenance.
  • You measure success by "it shipped" rather than "it shipped, it holds up, and the team trusts how we got there."
  • You've built a reputation for moving fast at the cost of the people around you — trust and speed both matter here, not one traded for the other.

Requirements:
  • 5+ years as a software engineer, with real ownership of production systems at a startup — you've designed and shipped systems end to end, not just contributed to systems someone else architected.
  • Fluency in Python or Go, with strong data modeling and system design instincts.
  • Experience building SaaS or multi-tenant systems, and the product judgment that comes with it.
  • A track record of solving hard, ambiguous engineering problems — untangling messy domains, making design decisions with incomplete information, and owning the outcome — not just building well-scoped features.
  • Fluent in AI-assisted development as a default way of working, and able to bring others along on it.
  • Evidence that other engineers and leaders trusted your judgment and wanted you on their hardest problems — examples that speak to this are a plus.

We’re a growing team that works collaboratively, supports each other, and is energized by having an impact. We value passion and the ability to learn — you’re encouraged to apply even if your experience doesn’t match the job description precisely!

The following is a representative annual base salary range for this position within the Bay Area: $170,000-$221,000. In addition, job level and salary opportunities are evaluated during our interview process — we review each applicant's experience, knowledge, skills, and abilities.

Instrumental is proud to offer a highly-rated variety of benefits, including health, vision, dental, commuter plans, and parental leave.

At Instrumental, protecting company and customer information is a shared responsibility. Employees are expected to comply with company engineering, security, access control, and privacy policies, and promptly report suspected security incidents or policy violations.
HQ

Instrumental Palo Alto, California, USA Office

909 Alma Street, Palo Alto, CA, United States, 94301

Similar Jobs

9 Minutes Ago
In-Office
198K-337K Annually
Expert/Leader
198K-337K Annually
Expert/Leader
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Own chip-level static timing analysis and sign-off for next-generation HBM SoCs through tape-out. Develop SDC constraints, drive timing closure across blocks and full-chip designs, perform MMMC, OCV, signal integrity, and crosstalk analysis, and automate STA workflows using Python and Tcl. Lead post-silicon timing correlation, define sign-off methodologies, communicate risks and readiness, and mentor junior engineers while collaborating across design, verification, physical design, test, and product teams.
Top Skills: 3D IcCadence TempusChipletsDftDramHbmJtagLiberty Timing ModelsMbistPythonSdcSynopsys PrimetimeTclTsv
10 Minutes Ago
In-Office
San Jose, CA, USA
154K-303K Annually
Senior level
154K-303K Annually
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Define validation strategies, coverage architectures, and scalable methodologies for next-generation data center SSDs. Analyze requirements, architectures, workloads, and validation gaps; develop risk-based coverage models; evaluate emerging technologies; and apply AI, analytics, automation, and LLMs to improve validation effectiveness. Partner across architecture, firmware, systems, product, and validation teams, present strategic recommendations, influence technical direction, and mentor engineers.
Top Skills: Agentic AiAutomationData AnalyticsData Center SsdDual PortEnterprise Storage SystemsFdpFirmwareGenerative AiLarge Language Models (Llms)Machine LearningNandNvmeOcp SsdQlcStorage PerformanceStorage ProtocolsVirtualization
10 Minutes Ago
In-Office
San Jose, CA, USA
196K-344K Annually
Senior level
196K-344K Annually
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Leads venture investment sourcing, evaluation, diligence, and execution across Seed through Series B. Drives company-wide AI and machine learning initiatives, maintains portfolio relationships, and develops executive, Board, and Investment Committee recommendations. The role requires technical fluency in AI or semiconductors, financial acumen, senior stakeholder influence, strategic judgment, team mentorship, and the ability to operate effectively in ambiguous, fast-paced environments.
Top Skills: Artificial IntelligenceData Center HardwareData Center SoftwareGenerative AiMachine LearningPhysical AiSemiconductor Technology

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account