Forward Deployer Engineer (AI-First)

About the role

• Work from the client’s office as part of the embedded Quash Team.
• Understand the client’s product, QA process, release cycle, and technical requirements.
• Build custom full-stack features, integrations, dashboards, and workflows for client use cases.
• Drive seamless adoption of Quash across client engineering, QA, and product teams.
• Develop AI-powered testing workflows and automation solutions based on client requirements.
• Debug issues across the Quash platform, client environments, and integrations.
• Convert client learnings into reusable best practices for future deployments.
• Coordinate with Quash’s internal product and engineering teams to improve the platform.

Requirements

AI & Integrations (core)

• Hands-on experience building AI-first product features with LLM APIs (OpenAI, Anthropic, Gemini, or similar) in production.
• Experience with agent orchestration frameworks — LlamaIndex, LangChain, or LangGraph.
• Strong understanding of prompt engineering, RAG, and vector databases (e.g. Qdrant, Pinecone, pgvector).
• Curiosity and willingness to experiment with emerging AI SDKs, models, and patterns.

Agentic Coding & AI-Native Workflow (core)
You don't just build with AI — you build using AI agents. As an embedded engineer, this is how you deliver like a small team on-site.

• Fluent across today's agentic coding tools, with a real opinion on tradeoffs — IDE agents (Cursor, GitHub Copilot agent mode), CLI agents (Claude Code, Codex CLI, OpenCode), and background/async agents (Devin, Copilot cloud agent). Tools listed as examples; the landscape shifts fast, so we value the durable skill over any single product.
• Strong context and workflow engineering: writing effective specs and rules files (e.g. CLAUDE.md, .cursorrules), scoping tasks an agent can actually finish, planning before executing, and wiring agents into real tools and data via MCP.
• Good judgment on when to let an agent run vs. when to hand-write — reviewing agent-generated code as rigorously as any human PR, and never shipping code you can't explain.
• Security discretion when embedded: knowing which tools send code to the cloud vs. run locally, respecting client data-residency and no-train policies, and defaulting to the client's approved toolchain.
• Comfortable using agents for high-leverage grunt work — test generation, migrations, debugging from stack traces, and fast repo onboarding.

Frontend

• Strong, senior-level experience with React.js, Next.js, TypeScript, and CSS.
• Solid command of modern JavaScript (ES6+) and component-based architecture.
• Experience with state management (Zustand, Redux, or Recoil) and React Hooks.
• Proficiency building responsive, performant, modular UIs, with frontend performance tuning.
• Comfort with API integration, auth flows, and secure client-side practices.

Backend

• Proficiency in Java (Spring Boot) for backend service development.
• Strong Python skills, including async programming and background/scheduled tasks.
• Deep understanding of RESTful API design and clean service architecture.
• Hands-on MongoDB experience: data modeling, schema design, indexing, and optimization.
• Solid grasp of authentication, authorization, and secure API practices (JWT/OAuth, secrets handling, idempotency).

Bonus / Nice-to-have

• Electron.js experience for cross-platform desktop apps (directly relevant to our app).
• Familiarity with AWS, Docker, and CI/CD pipelines.
• Experience with real-time systems (WebSockets, event-driven architectures).
• Background in Python web frameworks (FastAPI, Flask, or Django) for AI service APIs.
• Experience with mobile or device automation.