Full Stack Engineer

Swoon; Plano (TX); Vor Ort; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

Swoon is seeking a hands-on Senior Full Stack Engineer to design, build, and deploy scalable applications that leverage agentic AI and automation. You'll work across backend, frontend, and cloud infrastructure to deliver practical software solutions.

You will architect agentic AI workflows, integrate MCP-based components, and ensure secure API access to enterprise data sources, while collaborating with product and business teams.

Qualifikationen

• Production-grade backend and frontend experience.
• Experience deploying on AWS ECS and RDS.
• Experience with containerized development and CI/CD pipelines.
• Experience with agentic AI solutions, LLM-powered workflows, or AI-driven automation.
• Understanding MCP and secure access to tools and data.
• Familiarity with AI-assisted coding tools like Claude Code or Codex.

Aufgaben

• Design and implement agentic AI solutions and autonomous workflows.
• Build and integrate MCP servers, clients, tools, and context-aware workflows.
• Develop, deploy, and operate cloud-native apps on AWS (ECS, RDS).
• Package and deploy apps with Docker and implement CI/CD pipelines.
• Design and maintain RESTful APIs and integrations.
• Use AI coding tools to accelerate development and refactor code.
• Monitor and troubleshoot using CloudWatch and New Relic.
• Ensure security, testing, and scalable architecture.
• Collaborate with engineering, product, and business stakeholders.

Kenntnisse

Agentic AI

AWS

REST APIs

Docker

CI/CD

LLMs

Security best practices

Collaboration

Tools

Amazon ECS

Amazon RDS

CloudWatch

New Relic

Jobbeschreibung

We are seeking a hands-on Senior Full Stack Engineer with strong experience in backend development, modern frontend technologies, cloud infrastructure, and AI-powered automation. This role will design, build, and deploy scalable applications and intelligent agentic AI solutions that automate workflows, integrate with enterprise systems, and improve operational efficiency.

Key Responsibilities:

• Agentic AI Engineering: Design and implement agentic AI solutions, autonomous workflows, tool integrations, and intelligent automation using LLMs and MCP-based architectures.
• MCP Integration: Build and integrate MCP servers, clients, tools, and context-aware workflows that enable AI agents to interact securely with APIs, databases, and external systems.
• Cloud Infrastructure: Develop, deploy, and operate cloud-native applications on AWS, with hands-on experience using Amazon ECS and Amazon RDS.
• Containerization & Deployment: Package and deploy applications using Docker, implement CI/CD pipelines, and improve build, testing, release, and deployment automation.
• API Development & Integration: Design, build, and maintain secure, reliable RESTful APIs and service integrations that connect frontend applications, backend services, databases, and AI agents.
• AI-Assisted Software Development: Use AI coding tools such as Claude Code and OpenAI Codex to accelerate development, generate and refactor code, troubleshoot issues, automate repetitive engineering tasks, and improve developer productivity.
• Monitoring & Observability: Implement application monitoring, logging, alerting, and performance analysis using Amazon CloudWatch and New Relic to maintain reliability and troubleshoot production issues.
• Reliability & Security: Apply engineering best practices for authentication, authorization, error handling, testing, scalability, and secure handling of application data and AI tool access.
• Cross-Functional Collaboration: Partner with engineering, product, and business stakeholders to translate requirements into practical software solutions and deliver measurable automation outcomes.

Qualifications:

• Strong professional software engineering experience building and supporting production applications.
• Experience designing and integrating APIs, backend services, and distributed application components.
• Hands-on experience deploying and operating applications on AWS, particularly ECS and RDS.
• Experience with Docker, containerized application development, and CI/CD pipelines.
• Practical experience designing or implementing agentic AI solutions, LLM-powered workflows, or AI-driven automation.
• Understanding of MCP and how AI agents can securely access tools, APIs, and contextual data.
• Experience using AI-assisted coding tools such as Claude Code, Codex, or comparable development agents.
• Familiarity with production observability and troubleshooting using CloudWatch, New Relic, or similar monitoring platforms.
• Strong debugging, problem-solving, and communication skills, with the ability to work independently in a fast-paced engineering environment.

Preferred Qualifications:

• Experience deploying MCP-based applications and integrating AI agents with enterprise APIs, databases, and internal tools.
• Familiarity with LLM orchestration, tool calling, structured outputs, agent workflows, and human-in-the-loop controls.
• Experience with automated testing, infrastructure as code, and secure software delivery practices.
• Understanding of AI application security, including least-privilege access, secrets management, input validation, and prompt-injection risks.
• Experience optimizing application performance, cloud resource utilization, and engineering workflows through automation.