AI Full Stack Developer

BRUNT Workwear•North Reading, MA

2d•$130,000 - $160,000•Hybrid

About The Position

BRUNT is a fast-growing workwear brand built for the trades, and we are making a deliberate, strategic investment in artificial intelligence as a core driver of business performance, operational efficiency, and competitive advantage. As our AI Full Stack Developer, you will be the technical heart of that investment, the person who designs, builds, and evolves the AI solutions that BRUNT’s teams depend on to work smarter, move faster, and make better decisions. Reporting to the SVP of Technology within the DevOps team, you will serve as BRUNT’s principal AI engineering resource. You will own the design and development of a dedicated AI innovation environment within Google Cloud Platform, a sandbox project built for rapid prototyping and experimentation using Vertex AI, alongside a governed production GCP environment where approved AI solutions are deployed, maintained, and scaled for internal use. You will play a meaningful role in shaping how AI solutions are evaluated, approved, and governed, working as part of BRUNT’s AI Council on strategy and serving as a technical voice in the process of moving workloads from experimentation into production. Critically, this role extends beyond the codebase. You will be BRUNT’s internal AI expert and advocate, engaging directly with business teams across Merchandising, Operations, Retail, Finance, and beyond to workshop ideas, surface and prioritize use case opportunities, gather feedback on deployed solutions, and provide the guidance and practical training that helps BRUNT employees get real value from the AI tools they use every day. You will be the person the organization turns to when they want to understand what AI can do for them, and how to do it safely and well.

Requirements

6–8 years of full-stack software development experience, with a substantial, proven focus on deploying production AI/ML systems in the most recent phase of your career.
Hands-on experience with both Google Gemini (Vertex AI) and Anthropic Claude platforms, utilizing advanced orchestration tools like LangChain and LangGraph.
Proven track record designing and implementing Retrieval Augmented Generation (RAG) architecture, vector data stores, embedding pipelines, and agent frameworks.
Strong Python skills for backend services and API design (REST/GraphQL) paired with frontend capability (React, Next.js, or equivalent) to build internal tools end-to-end.
Practical experience with Google BigQuery, specifically designing AI-consumable data access patterns, semantic layers, and grounding strategies.
Experience managing separated GCP environments (sandbox vs. production) utilizing Terraform for infrastructure-as-code, following Git-based workflows within Agile/Jira sprint cadences.
Experience with Git-based version control workflows and Agile/Scrum sprint environments using Jira or comparable project management tools.
Exceptional ability to translate complex AI concepts to non-technical business teams, with proven success cross-functionally workshopping and requirement-gathering for new use cases.
Comfort operating as a senior individual contributor with a high degree of ownership and autonomy in a lean team.
Must be 18+ with full-time availability (including occasional off-hours support for critical production deployments) and the ability to reliably commute to the work location 4x per week.

Nice To Haves

Experience contributing to AI governance and responsible AI practices is a strong plus.
Familiarity with Shopify Plus, eCommerce platform architecture, or retail technology ecosystems is a meaningful advantage.

Responsibilities

Design and maintain a dedicated GCP sandbox for rapid prototyping (Vertex AI / Gemini Enterprise) alongside a secure, governed production environment.
Implement Terraform across all cloud projects to ensure reproducible, version-controlled, and auditable provisioning.
Design scalable patterns for internal tool deployment, including containerized services, managed APIs, and serverless compute.
Establish and maintain environment-level guardrails, access controls, and cost governance policies across both the sandbox and production GCP projects.
Build full-stack internal applications from concept to production, owning both backend logic and model integration across Claude Enterprise and Gemini Enterprise platforms.
Construct advanced automation solutions and internal agents using orchestration frameworks like LangChain and LangGraph.
Partner with the Data Engineer to build RAG pipelines, vector data stores, and a governed semantic layer over Google BigQuery.
Develop and maintain APIs, backend services, and frontend interfaces that surface AI capabilities to BRUNT employees in intuitive, production-grade internal tools.
Implement prompt engineering, evaluation, and optimization practices that ensure AI outputs are accurate, consistent, and aligned with BRUNT’s business requirements and brand standards.
Connect internal AI applications to data streams from critical operational platforms, including Shopify, NetSuite, and Deposco.
Serve as a technical voice on BRUNT's AI Council to help evaluate use cases, guide governance, and define approval criteria.
Establish the technical framework, testing standards, and rollback protocols for transitioning experimental workloads into production.
Ensure that all AI solutions in production meet BRUNT’s standards for security, data privacy, responsible AI use, and operational reliability.
Track deployed solutions for performance and accuracy, maintaining clear documentation of prompt libraries, model configurations, and codebases.
Partner directly with business teams to discover operational pain points and scope high-value AI solutions.
Serve as BRUNT’s internal AI expert and first point of contact for employees who want to understand how AI tools can support their work, providing clear, accessible guidance that translates technical capability into practical business value.
Deliver periodic practical training and enablement sessions to help BRUNT employees effectively use approved AI tools.
Work within BRUNT’s Agile sprint framework, managing AI development workload through Jira in 2–4 week cycles.
Maintain all application and infrastructure code in Git, following established branching, versioning, and documentation standards.