Agentic AI Engineer

Terms of Employment

• W2 Contract, 6 Months (Likely Extension)
• This is a hybrid position. The selected candidate should be comfortable working onsite once per week. There will be times where up to three days per week onsite may be required in critical moments.

Overview

As an Agentic AI Engineer, you will join a new, high-priority team at a leading firm, focused on integrating cutting-edge artificial intelligence into the core of their business applications. This is not a typical data science role. You will be a critical technical bridge, collaborating closely with a dedicated data science team to co-generate and build AI agents and models, and then using your application development expertise to weave them into the company's existing enterprise platform. This is a unique opportunity to shape AI strategy and build production-level systems from the ground up.

You will

• Collaborate with Data Scientists to identify business use cases and then co-generate, build, and optimize AI agents and models.
• Write production-level Python code to support AI agent communication and complex automation workflows.
• Integrate AI models and agents with internal and external services using APIs, leveraging your background in a Java-based environment.
• Connect AI systems to cloud platforms, specifically AWS, and databases.
• Support the full software development lifecycle, including testing, debugging, deployment, and monitoring of the agentic AI systems.

Required Qualifications

• Experience building production-level AI or Machine Learning systems, including LLMs and AI agents.
• 3+ years of hands-on, professional experience with Python and its data science libraries (e.g., Pandas, NumPy).
• 3+ years of professional software development experience using Java.
• Proven experience with AI agent frameworks such as LangChain, LangGraph, PyTorch, or TensorFlow.
• Must be located in or willing to commute to Reston, VA for a hybrid work schedule.

Preferred Qualifications

• Strong, hands-on experience with the Spring Framework, particularly Spring Boot, and developing RESTful services.
• Experience with CI/CD pipeline administration using tools like Kubernetes, Docker, or Jenkins.
• Familiarity with collaborative development platforms such as GitHub.