Senior Software Engineer

Vow is a cultured meat company on a mission to feed billions and create food that’s good for your tastebuds, your health and your planet. We’re bringing together cutting edge innovations in science, engineering, culinary and design to create new meats that meat lovers can choose selfishly because it’s nutritious and delicious, and we’re doing so in a sustainable way. Want to join us?

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The Role+

We're hiring a software engineer to build a software factory. The best manufacturing companies learned decades ago that you don't just build products, you build production systems. We think the same is true for software now.

Your job isn't to write every line of code. It's to design the codebase and guardrails, embed domain knowledge and feedback loops that let us reliably produce software for bioreactor control, process orchestration, and factory analytics. You'll encode our approach into reusable patterns and build validation systems that reject bad output before it reaches hardware or creates bad data.

This is full-stack in the truest sense. On any given week, you might be debugging a bioreactor control sequence on the factory floor, designing database schemas for process data, generating operator interfaces, or optimising real-time state estimation algorithms. The scope is unusually broad because our team is deliberately small and our ambition is not. You won't be handed a perfectly scoped backlog, you'll help decide what's worth building next, and increasingly, how we build.

You'll report to our Head of Software and work directly with process engineers, scientists, and operators. Your code will run on physical hardware that produces real food.

What You'll Build

• AI-driven development systems: Skills, commands, subagents, MCP servers, custom harnesses - you'll build the scaffolding that lets us (and non-SW engineers) reliably generate factory software and use our data.
• Control systems & orchestration: Python-based process control for bioreactors with safety guarantees. Hardware I/O via Modbus and OPC-UA. Coordinating multi-day production runs across dozens of devices.
• Operator interfaces: React frontends for machine control, process visualisation, and alarm management.
• Data & Infrastructure: PostgreSQL, MongoDB, Redis, Kafka, AWS. Design schemas, optimise queries, surface process insights.

How You'll Work

We ship daily. Small PRs, fast iteration, continuous deployment. The factory runs 24/7, and our software evolves with it.

We're genuinely curious how far AI-driven development can go. Claude Code, Codex, custom agents, MCP - we use them daily and want to push further. If you have ideas about how to 10x your own output, you'll have the freedom to try them here.

This is internal software with fast feedback loops, which means unusual room to experiment.

You'll spend meaningful time on the factory floor, understanding how operators interact with your systems, how devices behave under real conditions, and how process constraints shape requirements.

Collaboration is a constant. You'll work with bioprocess engineers and scientists, operators, data scientists and hardware engineers.

What Makes This Role Unusual

Ownership without gatekeeping. No architectural review board, no months-long approval process. You'll make significant technical decisions, own the outcomes, and iterate based on real-world results. The ceiling is whatever you're ready to carry.

Hardware in the loop. Your code runs on physical devices 50 meters from your desk. Write a control sequence on Monday, watch it run a production batch on Tuesday.

The problems are unsolved. How do you roll back a deployment mid-operation? How do you scale state estimation across dozens of bioreactors? We don't have all the answers, you'll help us find them.

Location and Work Style

Based at our facility in Sydney, Australia - converted warehouse with lab, factory floor, culinary center.

You'll work on-site at least 4 days per week, the factory is in Alexandria, and being physically present matters for debugging hardware integration, working with operators, and understanding the manufacturing context.

We don't track hours. We track outcomes.

Your Experience+

Must haves

• Strong software engineering fundamentals - clean code, sensible APIs, evolvable data models
• You've built and operated production systems
• Zero-to-one experience: shipped something where little existed before, made tradeoffs, left it maintainable
• Strong product instincts - you talk to users, distill problems, iterate

What your week might look like

• Heavy use of AI coding tools (Claude Code, Copilot, agents) to ship faster
• Debugging control logic on the factory floor, then refining the system that generated it
• Translating process engineering requirements into validation rules
• Reviewing outputs from systems you built, not just code you wrote

Useful background (not required):

• Process control concepts (PID, state machines, batch processes)
• Software that touches physical systems - or strong curiosity about it

Who Tends to Thrive Here

People who do well here enjoy being close to the real world, prefer speed over ceremony, and get energy from clarifying and shaping ambiguity into actionable plans.

They're strong software engineers first - clean abstractions, thoughtful APIs, pragmatic tests - but don't want to be siloed. They like understanding how hardware, operators, and business constraints shape good systems.

You communicate proactively. Working with scientists, operators, and engineers from different disciplines means translating between contexts constantly. And you're drawn to the mission: building software for a cultivated meat factory is harder than building another SaaS product. The constraint is that it has to work in the physical world.

If you want a well-defined lane and a predictable backlog, this isn't the role. If you want to become a better engineer - not just a better software developer - this is for you.

What you'll do+

• Contribute across the stack in two key domains: primarily data/business focused software (inventory, quality, scheduling, costing, reporting/visualisation, supply/demand) and automation/controls/factory software as needed. Own features end-to-end.
• Work directly with operators and engineers to observe workflows, validate quickly, and turn findings into simpler, faster internal tools with clear, measurable outcomes.
• Advance our low-cost cell-culturing platform: contribute to new capabilities (planning/scheduling, quality-by-design, smart utility scheduling), improve reliability/performance, and help unlock flexibility via model/UI improvements.
• Extend our data model & pipelines – stream, store, and aggregate real-time process data; surface insights in dashboards, link to operational data for context
• Integrate wisely – plug in third-party MES/ERP or ML services where they add value, and craft clean and simple APIs for internal consumers.
• Prototype fast, validate rigorously – iterate with minimal red tape while upholding safety, uptime, and quality standards.

Success is+

Within 3 months, you will:

• Complete onboarding on our data model, core services, and operational workflows; shadow operators on the factory floor.
• Ship value early: Deliver high impact improvements to users whilst building context; begin independently scoping and owning new functionality.
• Share a short “fresh perspective” note: quick wins, debt to pay down, and 1–2 medium-term bets.

Within 6 months, you will:

• Lead multiple projects from problem → design → implementation → validation (e.g., scheduling sub-systems, supply-demand matching, data-model improvements) with measurable impact on decision quality or cycle time.
• Drive software contributions to larger team-wide initiatives (e.g., scheduling or supply/demand upgrades, quality-by-design checks), coordinating closely with operators and engineers.
• Take ownership of critical subsystems in our stack - backlog, roadmap, observability - ensuring they remain reliable and evolvable.
• Develop a deep understanding of our architecture and begin proposing and driving data model or workflow improvements that improve reliability and usability.

Within 12 months, you will:

• Propose and prototype forward-looking improvements (e.g., closed-loop optimisation, simulation, or a high-leverage third-party integration) that materially shifts how we operate.
• Independently own iteration of our core data models - driving changes that improve reliability, traceability, and usability
• Deliver a cornerstone capability (e.g., planning/scheduling primitives, traceability/quality gates, smart utility optimisation, or tools that accelerate recipe prototyping in our pilot kitchen) that we rely on week-to-week.
• Mentor newer engineers on our patterns (APIs, data models, UI ergonomics), and raise the bar with cross-team deep-dives or design reviews
• De-risk the next phase of scale (more reactors, SKUs, or throughput) by proving a pattern or integration path.

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