Full-Stack Engineer

About the role

You'll sit squarely at the intersection of back‑end and front‑end, ensuring seamless integration between APIs, databases, UIs, and ML services. You'll design, build, and scale features end‑to‑end, especially our AI/ML‑powered experiences, while mentoring peers and driving architecture decisions. Core Tech & Tools Languages & Frameworks: Python, Node.js, React (TypeScript) Datastore: PostgreSQL Cloud & Infra: Google Cloud Platform, Airflow, Terraform, Docker, Kubernetes ML/AI: LLMs, RAG, prompt engineering

Responsibilities

• Architect and implement full‑stack features, from database schema to React components, optimized for scale and reliability.
• Build and maintain RESTful/GraphQL APIs, data pipelines, and distributed services in GCP.
• Integrate, prompt, and debug LLMs and generative AI tools; own RAG or fine‑tuning pipelines.
• Ensure front‑end and back‑end systems interoperate flawlessly, minimize friction, optimize data flow, and enforce contracts.
• Collaborate with product, research, design, and infra teams to define requirements, iterate rapidly, and ship production‑grade code.
• Monitor performance, reliability, and security.
• Mentor junior engineers through code reviews, architecture reviews, and shared best practices.

Requirements

• 5+ years of professional software engineering experience with end‑to‑end ownership in a full‑stack role.
• Deep expertise in Python, Node.js, React/TypeScript, and PostgreSQL.
• Able to be hands‑on with GCP, containerization (Docker/K8s), and building/supporting high‑traffic systems.
• Proven experience integrating AI/ML models (LLMs, NLP, RAG) into production apps.
• Familiarity or strong interest in working with MCP servers.
• Exceptional problem‑solving skills and a product mindset: you think deeply about UX, performance, and business impact.
• You sweat both technical details and end-user experience.
• Experience with multi‑step or agentic AI workflows.
• Background in AI infrastructure or tooling companies.
• Contributions to open‑source AI/ML projects.

Benefits

Additional Information

What we're building We're empowering small teams with technology that makes it easier to market and grow businesses. Our current focus is to help consumer brands shift from "workflow automation" to "agent management" within their marketing operations. Shadow is the AI coordination layer - providing shared AI memory, centralized agent control, and model orchestration for marketing teams. Why join Shadow? Product Ownership You'll ship production code daily and help steer key product and technical decisions. Shape the Engineering Culture You'll influence how we work-tools, processes, standards, and hiring. Work with Challenger Consumer Brands Talk directly to customers (CEOs, CMOs, VP's) of fast-growing consumer brands-some doing $80M-$500M in revenue. The agency behind the product Shadow is built alongside Darkroom - a performance marketing agency that's been operating for 10 years, employs 100+ people, runs 100+ clients at a time, and has worked with over 1,000 consumer brands. The agency is both our proving ground and our first user, which means the data you build with is real marketing data at real volume from day one - not a synthetic demo.

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Company Intel

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