Senior Full Stack Developer

Senior Full Stack Developer - AI & Data

Job Overview

We're hiring a Senior Full Stack Developer who works across backend engineering, data infrastructure, applied LLM systems, and SEO-optimized web builds. You'll build the APIs, pipelines, websites and dashboards that power our internal tools and client delivery - owning features end to end, from database migration to UI.

Comfort with AI coding tools and LLM APIs is essential, not optional. It's how we ship.

Key Responsibilities

Backend & APIs

• Build scalable services in Python (FastAPI/Django), containerized with Docker.
• Design REST APIs, including long-running jobs with streaming progress.
• Build dashboards and internal UIs in React, Next.js and TypeScript.

Cloud Infrastructure (GCP)

• Deploy and operate containerized services on Cloud Run - revisions, scaling, concurrency, cold starts, secrets.
• Manage Cloud Storage buckets for assets, reports and backups, with sane lifecycle and access policies.
• Provision and maintain Compute Engine VMs for long-running or non-containerized workloads.
• Set up recurring pipelines with Cloud Scheduler and job queues.
• Work with Secret Manager, IAM roles and service accounts, Artifact Registry, and Cloud Logging/Monitoring for debugging production.

Data Handling at Scale

• Ingest, clean and normalize large structured and unstructured datasets - CSVs, scraped web content, transcripts, PDFs, third-party API exports.
• Build extraction and enrichment pipelines that turn messy raw input into queryable, deduplicated records.
• Handle the unglamorous parts properly: entity resolution, canonical naming, missing and conflicting values, validation gates before data reaches a client.
• Keep pipelines resumable and auditable so a failed run can be traced and re-run, not restarted from zero.

SEO-Optimized Website Building

• Build fast, technically clean marketing sites in Next.js with a headless CMS (Payload).
• Own technical SEO: structured data (JSON-LD), sitemaps and robots, canonicals, metadata, internal linking.
• Optimize Core Web Vitals, rendering strategy and crawlability.
• Build for AI search visibility, not just Google rankings.

Databases

• Design and normalize PostgreSQL/Supabase schemas; write migrations by hand.
• Implement RLS, backups and access controls.
• Optimize queries and connection handling under concurrent load.

LLM Engineering

• Work across multiple providers through a unified gateway.
• Build structured-output flows, RAG and retrieval pipelines, and agentic workflows.
• Optimize cost and latency: prompt caching, model routing, token accounting.
• Treat hallucination as an engineering problem - build validation and evals, not vibes.

AI Coding Tools

• Daily, skilled use of Claude Code, Codex, Cursor or similar. Decompose tasks well, review output critically, and know when to write it yourself.
• Never ship generated code you can't explain.

Internal Team Enablement & Automation

• Sit with non-technical teams, map how they actually work, and find the manual steps worth automating.
• Turn those workflows into tools the team can run themselves - no engineer in the loop for routine runs.
• Write clear internal docs and walk teams through new tools; support and iterate after launch.
• Measure what you automated: time saved, errors avoided, throughput gained.

Integrations & Automation

• Integrate third-party APIs with rate limiting and failure isolation.
• Handle OAuth, JWT and service-to-service auth; manage SDK version drift.
• Automate manual workflows end to end - ingestion through to insight delivery.

Reporting & Analytics

• Build automated dashboards and client-facing PDF/HTML reports.
• Translate business goals into metrics and KPIs; investigate trends and anomalies.

Testing & Debugging

• Write real tests (pytest, Playwright, Vitest), including deterministic mocks for LLM code.
• Debug across the stack - job state, silent failures, provider timeouts, concurrency. Root-cause it.

Requirements

• 4+ years shipping production full-stack applications.
• Strong Python and PostgreSQL; solid React/Next.js/TypeScript.
• Hands-on GCP experience - Cloud Run, Cloud Storage, Compute Engine, Cloud Scheduler.
• Experience working with large, messy datasets - cleaning, normalizing and making them usable.
• Production experience with LLM APIs - RAG, structured outputs, cost optimization.
• Hands-on technical SEO experience on sites you've built and shipped.
• Fluent, critical use of AI coding assistants.
• Docker, Git, and a genuine testing habit.
• Comfortable working directly with non-technical teams.

Nice to have: pgvector/embeddings, Supabase, headless CMS (Payload/Sanity), marketing-analytics background.

Industry: Marketing Services · Employment Type: Full-time