Member of Technical Staff - Cloud Infrastructure

Unconventional, Inc.•Mountain View, CA

12h

About The Position

As the first hire and zero-to-one owner of Unconventional AI’s Agentic Applications pod, the Member of Technical Staff will serve as the founding engineer for the company’s internal enterprise productivity suite. This highly autonomous role is responsible for architecting and developing bespoke applications using Agentic AI to accelerate business operations, including intelligent recruiting tools, dynamic knowledge bases, contextual AI assistants, and semantic search. The role will shape technical strategy, guide build-versus-buy decisions, and establish how AI agents support day-to-day operations. The position includes full lifecycle ownership of applications, using the Databricks Apps platform to streamline deployment, hosting, and scaling. The engineer will work directly with internal stakeholders to gather requirements, prototype quickly, gather feedback, and prioritize the product roadmap, while evaluating developments in the AI ecosystem to deliver effective internal tools.

Requirements

Bachelor of Science in Computer Science or equivalent practical experience.
At least 5 years of full-stack software engineering experience across frontend and backend development.
Strong programming proficiency in Python and/or modern JavaScript ecosystems, such as Node.js, React, or Next.js.
Hands-on experience building agentic applications, including LLM orchestration with LangChain or similar frameworks.
Solid database fundamentals and practical experience with both SQL and vector databases.
Experience with DevOps practices, CI/CD, and end-to-end operational ownership of application deployment.
Comfort using AI coding assistants such as Cursor, Claude Code, or Codex as part of an AI-native development workflow.
Provide demoable personal or past projects showcasing relevant full-stack or AI-driven builds.

Nice To Haves

Experience developing enterprise applications, particularly internal productivity or operations tools.
Deep understanding of application security, including authentication protocols such as SSO, OAuth, or SAML, and robust access controls.
Expertise designing and deploying robust RAG pipelines and using advanced prompt-engineering techniques.
Hands-on experience deploying, scaling, and maintaining applications in major cloud environments such as AWS, GCP, or Azure.
Familiarity with machine learning or silicon engineering.

Responsibilities

Architect, build, and maintain bespoke internal enterprise productivity applications powered by Agentic AI, such as recruiting tools, contextual assistants, and semantic search.
Own applications throughout their lifecycle and use the Databricks Apps platform to support deployment, hosting, scaling, reliability, and performance.
Work autonomously with internal stakeholders to gather requirements, rapidly prototype, collect feedback, and prioritize the roadmap.
Evaluate the evolving AI ecosystem and lead build-versus-buy decisions for internal tooling.
Set technical strategy and establish how AI agents augment day-to-day company operations.