Software Engineer

Who you are

• 1-3 years of experience building and owning production systems in high-growth startups or similarly demanding environments
• Strong experience working with APIs, integrations, authentication systems, and event-driven architectures
• Proven ability to debug complex systems in production
• Comfortable operating in ambiguous environments where documentation is incomplete, and requirements evolve quickly
• Strong communication skills and the ability to build trust with technical and non-technical stakeholders
• Experience working directly with customers is a strong plus

What the job involves

• We’re hiring a Software Engineer, Agent Delivery to deploy production AI agents inside some of the world’s largest supply chain companies
• You’ll work directly with customer operators, engineers, and executives to understand how critical workflows actually run
• Then you’ll design integrations, debug production systems, and ship AI-powered workflows into environments that are often undocumented, fragmented, and business-critical
• This role sits at the intersection of engineering, product, and customer operations
• You’ll own deployments from initial discovery through production launch, spending time with customers both remotely and onsite, solving complex operational problems and turning those solutions into reusable product capabilities
• Success in this role is measured by outcomes: can you get systems live, make them reliable, and solve problems in environments you don’t fully control? Every deployment teaches us something new about how supply chain companies operate
• The patterns you uncover become product features, and what you solve for one customer often becomes a capability we ship across the platform
• Production Agent Delivery: Lead high-impact customer deployments from problem definition through production. Design and build production-grade AI agents, workflows, integrations, and supporting infrastructure that solve real customer problems and operate reliably at scale
• Transformational Customer Impact: Partner with customers to identify workflows where AI agents can fundamentally change how work gets done. Own the technical delivery from end-to-end design and prototyping through implementation, evaluation, deployment, and iteration
• Turn Ambiguity into Working Software: Embed deeply in customer workflows, understand how their teams and systems actually operate, and translate messy business requirements into clear technical solutions. Move quickly from an idea or manual process to a production system delivering measurable value
• Own the Architecture: Make architecture and design decisions across agent behavior, application logic, data, integrations, evaluations, security, and reliability. Ensure solutions meet customer requirements while establishing strong patterns for how Pallet agents should be deployed in production
• Integrate Into the Customer Stack: Connect Pallet agents to the systems, data, APIs, and tools customers already rely on. Work directly with customer engineering and operations teams to navigate technical constraints and make Pallet a reliable part of their production workflows
• Own Production Outcomes: Stay accountable beyond the initial build. Debug failures, improve agent quality, evaluate performance, and work across Pallet Engineering and Product to rapidly resolve issues that stand between a customer and a successful deployment
• Customer Immersion: Build relationships across the customer organization, from technical ICs and operators to executives. Develop a deep understanding of their workflows, constraints, and goals so that what you build solves the underlying problem—not just the initial request
• Build Once, Scale Many Times: Turn lessons from individual deployments into reusable agents, integrations, evaluations, frameworks, and implementation patterns. Help Pallet move from bespoke customer work toward repeatable products that can be deployed across many customers
• Shape the Product: Serve as a tight feedback loop between customers and Pallet’s Product and Engineering teams. Identify recurring needs, product gaps, and opportunities uncovered in the field, and help turn them into improvements to the core Pallet platform
• Our Tech Stack:
• Backend: Node + TypeScript on Encore.dev. Event-driven design with message passing and queues. Hosted on GCP
• Database: PostgreSQL
• LLMs: OpenAI, Anthropic, Google for foundation models; fine-tuned models on Vertex AI
• Browser Automation: Playwright
• Frontend: Next.js + React + TypeScript. Hosted on Vercel
• Observability: Datadog for logging and metrics

Benefits

• 🩺 Health, Vision and Dental benefits
• 🏝️ Flexible PTO
• ➕ Life Insurance and Accidental Insurance
• ❤️‍🩹 Short-Term Disability Coverage
• 💸 Equity for all staff
• 🪜 401k option; helping you save for the future
• 📚 Yearly learning and development stipend
• 🚌 Commuter benefits if you live in SF
• 🚘 Fully covered uber ride home if you ever have to work late in the office
• 🏡 Remote office home stipend
• 🥤 Monthly happy hours; our last one was a Golden Gate Park BBQ
• 🍲 Company paid dinners on Tuesdays and Thursdays in the office
• 🎉 Annual Company Offsites; our last one was in Sonoma Wine Country 🍷