AI Engineer – Full-Stack (Forward Deployed)

Remote · USD 65,000-85,000 · 3+ years experience · Remote · Posted Oct 7, 2026

At a glance

Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.

Gruve is hiring an AI-native full-stack engineer who works directly with business teams and owns each solution end to end, from the first conversation to production.
This role follows the Forward Deployed Engineer (FDE) model: embedded with the business, close to the users, and accountable for the outcome and the date.
You will take a business problem, design and build the solution yourself, and ship it to production against fixed, short deadlines.

Work directly with business stakeholders to map their workflows, pain points and the cost of the current process.
Use AI research tools to quickly benchmark industry standards, regulations and best practices for the process.
Turn unclear requests into a defined problem, scope, success measure and delivery date, and push back early when scope doesn't fit the timeline.
Build and demo a working POC within the first couple of days, using AI to generate scaffolding, UI, data models and integrations in hours.
Develop full-stack solutions including web apps, AI agents, multi-step workflow automations, integrations and data pipelines.
Run AI-driven development workflows by writing precise specs and prompts, breaking work into tasks for the AI, running parallel agents, and reviewing their output.
Use AI to generate unit, integration and end-to-end tests, review code, find bugs and produce documentation.
Prepare information security, data privacy and legal documentation and see the reviews through.
Raise and manage change requests through the change control process and deploy to enterprise cloud environments with SSO, access control, logging and monitoring.
Train users, produce concise user and support guides, get business sign-off, and run several projects at once on staggered timelines.

Expert daily use of AI coding tools such as Claude Code, Cursor, or Copilot, including agentic, multi-file and multi-step development.
Prompt and context engineering experience including system prompts, structured outputs, few-shot design, and managing the context window.
LLM application patterns experience including RAG, tool use or function calling, agents and multi-agent orchestration, and MCP servers and connectors.
Evaluation and guardrails experience including test sets, output validation, hallucination checks, prompt injection and data-leakage defences, and human-in-the-loop design.
Working knowledge of model selection, latency, token cost and rate-limit trade-offs across major LLM APIs like Anthropic, OpenAI, or Azure OpenAI.
Front end experience with React or TypeScript and responsive UI and component libraries.
Back end experience with Python (FastAPI/Flask) or Node.js, REST/GraphQL APIs, and async and background jobs.
Data experience with SQL and NoSQL databases, data modelling, ETL, and basic analytics and reporting.
Cloud deployment experience on Azure, AWS, or GCP utilizing app services, containers, or serverless functions.
3+ years building and shipping full-stack applications to production.

Previous FDE, solutions engineering, technical consulting or internal-tools experience.
Experience in a regulated industry such as healthcare, life sciences, manufacturing, or finance, and familiarity with GDPR, ISO 27001, SOC 2, or GxP.
Experience building internal AI platforms, shared skill libraries or reusable agent frameworks.
Python data tooling including pandas and notebooks, and basic machine learning familiarity.

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