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.