Systems Engineer, Platform Engineering

Quanta Services Management Partnership•Houston, TX

About The Position

Platform Engineering builds and operates the internal platforms that support Quanta’s IT Transformation, including self-service cloud provisioning, an AI assistant serving as the front door to IT, and the integrations that power them. This is a hands-on development role focused on building full-stack features, shipping applications on Databricks, and extending AI-assisted tooling. The role is delivery-focused and suited to someone comfortable working across frontend, backend, and applied AI without needing deep specialization in each area. The engineer will work alongside senior engineers who provide context and direction, and will carry assigned work from ticket to production with minimal hand-holding.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related field; equivalent experience is considered.
2–4 years of professional software development experience.
Full-stack development experience with TypeScript or JavaScript, React, Vite, Node.js, and Fastify or a comparable Node framework.
Working experience with GitHub, including Git workflows and GitHub Actions.
CI/CD pipeline experience building, maintaining, or troubleshooting automated build and deployment pipelines.
Some hands-on exposure to Databricks, or comparable data-platform experience and the ability to ramp quickly.
Some exposure to AI/LLM application development, such as RAG, vector databases, MCP, or agent frameworks like LangGraph, and a genuine interest in developing this skill set.
Ability to work across a broad technical surface without deep specialization in every layer.
Ability to execute assigned work to completion, raise blockers early, learn quickly, ask good questions, and document work.

Nice To Haves

Production experience with Databricks Apps, rather than only Databricks notebooks or jobs.
Hands-on experience building or consuming MCP servers.
Experience with vector databases or embedding-based semantic search.
Familiarity with Azure as a secondary cloud.
Exposure to container workflows such as Docker, ECR, or Kubernetes basics.
AWS cloud infrastructure experience, including basic infrastructure as code, is preferred.

Responsibilities

Build and maintain frontend features using React and Vite, translating design and product requirements into shipped user interfaces.
Develop backend services and APIs with Node.js and Fastify, including authentication, data access, and integration endpoints.
Write typed TypeScript and JavaScript across the stack and participate in code review.
Contribute to shared component and service patterns used across internal platforms.
Build and deploy applications on Databricks Apps, including data-backed workflows and internal tools.
Use Databricks-hosted data sources and jobs to power application features.
Support and extend AI-assisted tooling, including RAG pipelines, vector search, and agentic workflows.
Implement and consume MCP servers for integration and tooling work.
Contribute to LangGraph-based agent flows under senior engineers’ direction.
Provision and manage cloud infrastructure as code using tools such as Terraform, CDK, or CloudFormation.
Build and maintain GitHub Actions workflows and contribute to CI/CD pipelines across team repositories.
Deploy and operate workloads on AWS, working with compute, networking, and IAM services.
Implement and maintain monitoring, logging, and observability for services.
Participate in operational support for systems built by the team.
Complete assigned work, raise blockers early, learn from senior engineers, and document work through code comments, READMEs, and short decision notes.