Full Stack AI Engineer

About the Role

We are seeking a Full Stack AI Engineer to design, build, and deploy AI-powered applications that transform customer and employee experiences through intelligent automation. This is a hands-on engineering role responsible for developing modern AI solutions that streamline business processes, improve decision-making, and integrate seamlessly with enterprise systems.

The ideal candidate is equally comfortable building backend AI services, developing modern web applications, integrating enterprise platforms, and deploying scalable cloud-native solutions.

Responsibilities

Design, build, and deploy AI-powered applications using modern LLMs, agent frameworks, and Retrieval-Augmented Generation (RAG) architectures.

Develop full stack solutions, including responsive frontends, scalable backend APIs, and AI services that integrate seamlessly with enterprise platforms.

Build and optimize data pipelines, semantic retrieval, document processing, and vector search solutions that power intelligent AI experiences.

Integrate AI applications with Salesforce and other business systems through APIs and workflow automation.

Collaborate with business stakeholders to translate business requirements into secure, scalable, and user-friendly AI solutions.

Own the full software development lifecycle, including architecture, testing, deployment, documentation, and continuous improvement.

Required Qualifications

5+ years of experience as a Full Stack Software Engineer or AI Engineer building production applications.

2+ years of experience developing Generative AI or LLM-powered applications.

Strong proficiency in Python and modern software engineering best practices.

Hands-on experience with Databricks for AI, machine learning, or data engineering workloads (required).

Experience building AI applications using the Vercel AI SDK (required).

Strong experience with React, Next.js, JavaScript, and/or TypeScript.

Experience designing and developing RESTful APIs and backend services.

Experience with RAG, vector databases, embeddings, prompt engineering, and AI agent architectures.

Experience integrating enterprise applications through APIs.

Familiarity with Salesforce integrations (developer experience not required).

Experience deploying applications to Azure, AWS, or GCP.

Strong communication skills and Agile experience.

Preferred Qualifications

Experience building AI copilots, assistants, or workflow automation solutions.

Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.

Experience with document intelligence, OCR, and document processing.

Familiarity with Canvas, HubSpot, Kira, or similar SaaS platforms.

Experience implementing AI monitoring, evaluation, and governance.

Experience in education, nonprofit, or other mission-driven organizations.