Systems Engineer, Platform Engineering

Quanta Services•Houston, TX

About The Position

Platform Engineering builds and operates the internal platforms Quanta’s IT Transformation runs on, including self-service cloud provisioning, an AI assistant that serves as the front door to IT, and the integrations that power them. This is a hands-on development role on the Platform Engineering team, building full-stack features, shipping apps on Databricks, and extending AI-assisted capabilities in the team’s tooling. The role is delivery-focused and suited to someone comfortable working across frontend, backend, and applied AI without needing deep specialization in every layer. Senior engineers provide context and direction, while the engineer is expected to take 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, including building, maintaining, or troubleshooting automated build and deployment pipelines.
Some hands-on exposure to Databricks, or comparable data-platform experience with 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 these skills.
Ability to execute assigned work to completion and raise blockers early.
Comfort working across a broad technical surface without deep specialization in every layer.
Ability to ask good questions, learn quickly from senior engineers, and document work.

Nice To Haves

AWS cloud infrastructure experience, including basic infrastructure as code using Terraform, CDK, CloudFormation, or similar tools.
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.

Responsibilities

Build and maintain frontend features using React and Vite, translating design and product requirements into shipped UI.
Develop backend services and APIs on Node.js with Fastify, including authentication, data access, and integration endpoints.
Write clean, typed TypeScript and JavaScript across the stack, participate in code review, and contribute to shared component and service patterns.
Build and deploy applications on Databricks Apps, including data-backed workflows and internal tooling.
Use Databricks-hosted data sources and jobs to power application features.
Support and extend AI-assisted features, including retrieval-augmented generation pipelines, vector search, and agentic workflows.
Implement and consume MCP (Model Context Protocol) servers as part of integration and tooling work.
Contribute to LangGraph-based agent flows under the direction of senior engineers.
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 built.
Participate in operational support for systems built.
Complete assigned work, raise blockers early, learn from senior engineers, and document work through code comments, READMEs, and short decision notes.