Full Stack Engineer

Mandatory Areas
Must have skills.
Python & SQL
MCP servers
APIs and SDKs
MCP servers

About the role client is hiring Full Stack Engineers to build an internal AI platform that streamlines day-to day work across Sales, Content Marketing, and Engineering. The platform is the foundation for building, deploying, and governing AI-powered workflows across the organization. The work includes hosting and running MCP servers, developing AI workflow capabilities, implementing secure auth patterns, and enabling teams to safely connect AI agents to approved tools, systems, and resources. This role suits engineers excited about practical AI applications, developer platforms, and reusable foundations that help teams work more efficiently.

What You'll Do
• Build and extend an internal AI platform for creating, deploying, and managing AI-powered workflows using FastMCP.
• Develop full stack applications and services in Python.
• Build infrastructure to host, deploy, and operate MCP servers.
• Implement secure auth patterns to govern access to tools, data, and business resources through MCP.
• Design, implement and maintain AI workflows that streamline repetitive, tedious, or time consuming business tasks using FastMCP
. • Develop secure integrations with internal systems, external APIs, and AI model providers.
• Build and maintain CI/CD pipelines (GitHub Workflows/Actions) for reliable, repeatable deployments.
• Use AWS CloudFormation and/or AWS CDK to manage infrastructure as code.
• Collaborate with stakeholders across Sales, Content Marketing, and Engineering to translate workflows into scalable technical solutions.
• Help define best practices for building, deploying, securing, and operating AI workflows across the organization.
Python & SQL Must-Haves You will not be a fit without all of the following:

Strong full stack development with Python.
Proficiency with SQL for querying, analyzing, and integrating data from relational databases.
Proficiency with docker/containerized workloads in AWS.
Building, deploying, and maintaining cloud-based applications on AWS. E.g. ECS, Lambda, AgentCore.
Infrastructure as code with AWS CloudFormation and/or AWS CDK.
CI/CD pipelines using GitHub Workflows and Actions.
Building AI-powered applications, automations, agents, or workflow tools.
Developing or integrating with MCP servers, tool-calling systems, or similar plugin architectures.
Hands-on work with AI model APIs and SDKs. Any of the following FastMCP, OpenAI SDK, Claude SDK, Vercel AI SDK, or AWS Strands.
Active use of AI-assisted coding tools such as Cursor, Claude Code, Codex, or OpenCode.
Implementing secure authentication, authorization, and access-control patterns.