Firmable is the market-leading B2B sales intelligence platform in Asia-Pacific. Our competitive moat is our data: the deepest, most localised company and people dataset in every market we operate in. We've proven the model in ANZ. Now we're scaling it across Southeast Asia and the US.

Our platform runs on AI. This role builds the features that put intelligence into customers' hands every day.

The Role

Senior Full Stack Engineer (AI) ships end-to-end features across our stack: database to frontend to integrations. You'll own work from spec to production, and you'll work alongside product, design, and our Australian engineering team. AI isn't a feature you'll add; it's foundational to how you think about what you build.

This is not a "full stack" role where you pick a layer and own it deeply. It's an ownership role where you move across the whole stack fluidly, making the calls that get features live fast and right.

Reporting to Engineering Lead, based in Melbourne (hybrid, flexible).

~75% hands-on execution: shipping features across web, API, browser extension, and integrations; building durable background jobs and webhooks; designing APIs and data flows across Postgres, OpenSearch, DynamoDB and S3; building AI-native features using Mastra, CopilotKit, and LLM APIs.

~25% strategy: technical specs, architecture decisions, code review rigor, and clear communication of trade-offs to engineers and non-engineers alike.

What You'll Own

Feature shipping

• Full stack execution: build and ship features across our customer web app (Next.js), API layer (TypeScript), browser extension, and third-party integrations

• Data and backend design: design APIs and data flows across Postgres (Supabase), OpenSearch, DynamoDB and S3; build durable background job syncs, bulk enrichment, scheduled jobs and webhooks

• Quality standards: keep the codebase typed, tested, and observable; own code review and shipping discipline

AI features

• Agentic systems: build autonomous tools and copilots using frameworks like Mastra and CopilotKit

• LLM integration: ship with Claude, OpenAI, and other LLM APIs; implement features like tool calling, RAG, agents, structured output and evaluations

• CRM integrations: extend our integrations across HubSpot, Salesforce, and emerging integration platforms (Nango, Paragon)

Technical leadership

• Specifications: write clear specs that explain trade-offs and scope

• Collaboration: communicate technical decisions clearly to engineers and non-technical stakeholders; raise risks early

What We're Looking For

Must Haves

• 5+ years shipping production web and Next.js: you've built real products end to end and shipped them at scale

• Strong backend fundamentals: REST API design, relational data modelling in Postgres, auth and multi-tenancy patterns, background job architecture

• Agentic AI hands-on: you've shipped features using LLMs (tool calling, RAG, agents, structured output, evals); you can explain what broke and how you debugged it

• AI-native workflow: you use Claude Code, Cursor or similar as your default way of working, every day. You plan, delegate, review and verify AI output thoughtfully

• Very good communication: clear written English in async updates, technical specs, and PR descriptions; confidence in conversations with stakeholders; you raise risks early

• Ownership mindset: you take ambiguous problems through to shipped, measurable outcomes

• You live and breathe AI tools. You use AI daily for API design, debugging, code review, test coverage, and architectural thinking as your default way of working, not a productivity experiment. In 2026, this is how strong engineers move fast, and you need to already be doing it.

Highly Valued

• Monorepo experience: Turborepo or equivalent; Tailwind with Radix/Shadcn design systems; TanStack Query and Zustand

• Authentication and billing: Clerk (organisations and RBAC), Stripe usage-based billing

• AWS and infrastructure: Lambda, OpenSearch, DynamoDB, experience shipping at scale

• Browser extensions: Plasmo or similar framework; Chrome extension patterns

• Building MCP servers or evaluation and observability frameworks for agents

• Startup or scaleup background where you've had to build the standard, not inherit it

The Environment

Firmable runs lean and ships fast: small senior teams, no layers, minimal process. You'll work closely with a co-located engineering team in Melbourne and ship multiple features per cycle. There's no separate "AI team": you own the full scope from spec to production, with your team as your sounding board.

We are an AI-native organisation. That means AI isn't a tool we reach for: it's the default operating mode. You'll use AI for API design and data modelling decisions, for debugging and test coverage, for code review and architectural thinking, and for evaluating LLM outputs in production. If you're not already working this way, this role isn't right for you.

Why This Role

• Full ownership: you own features from spec to production across the entire stack. No handoffs, no "throw it over the wall" moments.

• AI at the core: building agentic systems and copilots isn't a side project; it's foundational to the product. You'll ship AI features every quarter, not once a year.

• Real career runway: as the platform scales and the team grows, you can move into technical leadership, architecture, or build a specialisation in AI systems. The ceiling is set by output, not tenure.