Generative AI Engineer

Swoon; McLean (VA); On-site; USD 120,000 - 160,000; Full time

Job summary

Swoon is seeking a GenAI/AI Agent Engineer to design, develop, and deploy scalable AI-powered applications and agentic workflows. You will implement LangGraph-based solutions, build multi-step reasoning workflows, and connect AI agents to enterprise systems with MCP servers and tools.

The role requires hands-on work with GenAI tools, LLMs, APIs, and production-grade CI/CD pipelines. You'll write Python and Java code, integrate APIs, and help ensure robust testing, monitoring, and deployment

Qualifications

• Hands-on experience with LangGraph and agent workflow orchestration.
• Experience with Model Context Protocol (MCP) and integrating AI agents with tools or external systems.
• Strong understanding of GenAI tools, LLMs, APIs, and AI application development.
• Experience with prompt engineering, including designing, testing, and optimizing prompts for LLM applications.
• Experienced in Java development and integrating AI solutions with Java-based applications.
• Experience building and maintaining CI/CD pipelines.
• Strong understanding of software engineering principles, APIs, debugging, testing, and deployment.

Responsibilities

• Design and develop GenAI-powered applications and AI agents using LangGraph.
• Build agentic workflows that support multi-step reasoning, tool calling, orchestration, and state management.
• Develop and integrate MCP servers, tools, and resources to connect AI agents with enterprise systems.
• Leverage GenAI tools, LLMs, APIs, and supporting frameworks to build production-ready AI solutions.
• Develop and optimize prompts, system instructions, and agent workflows to improve accuracy and reliability.
• Write clean, scalable Python code for AI/ML and backend applications.
• Work within Java-based applications and services, integrating AI capabilities into enterprise platforms.
• Develop APIs and integrations between AI agents, applications, databases, and enterprise systems.

Skills

LangGraph

Model Context Protocol (MCP)

GenAI tools

Prompt engineering

Python

Java

CI/CD pipelines

Testing

Tools

Docker

Kubernetes

Git

Job description

We are seeking a GenAI / AI Agent Engineer to design, develop, and integrate intelligent AI-powered applications and agentic workflows. The ideal candidate will have strong hands-on experience with LangGraph, Model Context Protocol (MCP), GenAI tools, prompt engineering, and Python, along with experience working in Java-based environments and CI/CD pipelines.

This role will focus on building scalable AI solutions, developing agent workflows, integrating tools and external systems, and deploying GenAI applications into enterprise environments.

Key Responsibilities

• Design and develop GenAI-powered applications and AI agents using frameworks such as LangGraph.
• Build agentic workflows that support multi-step reasoning, tool calling, orchestration, and state management.
• Develop and integrate Model Context Protocol (MCP) servers, tools, and resources to connect AI agents with enterprise systems and external services.
• Leverage GenAI tools, LLMs, APIs, and supporting frameworks to build production-ready AI solutions.
• Develop and optimize prompts, system instructions, and agent workflows to improve accuracy, reliability, and overall model performance.
• Write clean, scalable, and maintainable Python code for AI/ML and backend applications.
• Work within Java-based applications and services, including integrating AI capabilities into existing enterprise platforms.
• Develop APIs and integrations between AI agents, applications, databases, and enterprise systems.
• Implement testing, monitoring, logging, and error handling for GenAI and agentic applications.
• Build and maintain CI/CD pipelines to automate application testing, deployment, and release processes.
• Collaborate with software engineers, architects, product teams, and other stakeholders to translate business requirements into AI-powered solutions.
• Troubleshoot and optimize AI applications across development, testing, and production environments.
• Stay current with emerging GenAI, agentic AI, LLM, MCP, and AI development technologies.

Required Qualifications

• Strong experience with LangGraph and agent workflow orchestration.
• Hands-on experience with Model Context Protocol (MCP) and integrating AI agents with tools or external systems.
• Strong understanding of GenAI tools, LLMs, APIs, and AI application development.
• Experience with prompt engineering, including designing, testing, and optimizing prompts for LLM applications.
• Experience with Java development and/or integrating AI solutions with Java-based applications.
• Experience building and maintaining CI/CD pipelines.
• Strong understanding of software engineering principles, APIs, debugging, testing, and deployment.
• Ability to work in a collaborative Agile/enterprise development environment.

Preferred Qualifications

• Experience building multi-agent or tool-using AI systems.
• Experience with LLM providers such as OpenAI, Anthropic, Google, or Azure OpenAI.
• Experience with vector databases, RAG, embeddings, and knowledge retrieval.
• Experience with REST APIs and microservices.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Docker, Kubernetes, Git, and infrastructure automation.
• Experience with AI application evaluation, observability, guardrails, and production monitoring.

Core Technology Stack

AI / GenAI: LangGraph, MCP, LLMs, GenAI Tools, Prompt Engineering

Programming: Python, Java

Development: APIs, Agentic Workflows, Tool Calling, AI Integrations

DevOps: CI/CD, Git, Automated Testing, Deployment