AI Agent Developer x3

Qualifications

• 5+ years of experience as a software developer designing, coding, testing, and deploying applications in enterprise-level environments
• 3+ years of experience in AI Agent Development and Prompt Engineering, building end-to-end agentic workflows including state management, orchestration, and integration with LLMs
• Proficient in Python programming, with the ability to write clean, scalable, and production-ready code
• Hands-on experience with AI agent frameworks (LangChain, LangGraph, or LlamaIndex) to design, implement, and maintain autonomous agent systems
• Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) for building intelligent data-driven agent workflows
• Strong collaboration and communication skills, with the ability to work effectively in a highly team-oriented environment
• Working experience with ML libraries/tools (PyTorch, TensorFlow, Sklearn)
• Familiarity with docker containers and container services (AWS ECS, AWS EKS, Kubernetes)
• Knowledge of computer vision and machine learning algorithms (regression, neural networks, deep learning, XGBoost)
• Experience building full machine learning systems including model training, model inference, and model monitoring
• Background in Data Science, NLP, or Knowledge Engineering

Responsibilities

• These agents will analyze global rules, regulations, and compliance requirements, then translate that intelligence into policies that drive payroll operations across ADP’s platform
• Design, develop, and deploy AI agents using frameworks such as LangChain, LangGraph, CrewAI, or Strands
• Build full end-to-end AI agent workflows, including orchestration, state management, and integration with data pipelines
• Implement advanced agent design patterns (e.g., ReAct, Chain-of-Thought, Tree of Thoughts) for scalable and efficient agent systems
• Develop clean, scalable, and production-ready code in Python
• Integrate LLMs with traditional systems for hybrid intelligence solutions
• Apply advanced prompt engineering in collaboration with SMEs to drive accurate, context-aware agent performance
• Work in a team-first environment, contributing to design sessions, knowledge sharing, and peer reviews
• Support innovation by staying current with the latest advancements in GenAI and agentic frameworks

Full Description

Job Description:

The ADP Payroll Innovation team is building a new initiative focused on creating autonomous agent systems to support country-level research and policy automation.

These agents will analyze global rules, regulations, and compliance requirements, then translate that intelligence into policies that drive payroll operations across ADP’s platform.

This is a Greenfield effort – there are no existing systems to maintain, and the team is designing every component of the agentic workflows.

This is an exciting opportunity to join a high-impact team at the forefront of AI innovation, working with modern frameworks to develop intelligent systems that reason, collaborate, and make decisions at scale for millions of ADP customers!

Requirements:

• 5+ years of experience as a software developer designing, coding, testing, and deploying applications in enterprise-level environments.

• 3+ years of experience in AI Agent Development and Prompt Engineering, building end-to-end agentic workflows including state management, orchestration, and integration with LLMs.

• Proficient in Python programming, with the ability to write clean, scalable, and production-ready code.

• Hands-on experience with AI agent frameworks (LangChain, LangGraph, or LlamaIndex) to design, implement, and maintain autonomous agent systems.

• Experience working in a cloud environment (AWS preferred), including deploying and scaling applications.

• Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) for building intelligent data-driven agent workflows.

• Strong collaboration and communication skills, with the ability to work effectively in a highly team-oriented environment.

Nice to have:

• Working experience with ML libraries/tools (PyTorch, TensorFlow, Sklearn).

• Familiarity with docker containers and container services (AWS ECS, AWS EKS, Kubernetes).

• Knowledge of computer vision and machine learning algorithms (regression, neural networks, deep learning, XGBoost).

• Experience building full machine learning systems including model training, model inference, and model monitoring.

• Background in Data Science, NLP, or Knowledge Engineering.

Responsibilities:

• Design, develop, and deploy AI agents using frameworks such as LangChain, LangGraph, CrewAI, or Strands.

• Build full end-to-end AI agent workflows, including orchestration, state management, and integration with data pipelines.

• Implement advanced agent design patterns (e.g., ReAct, Chain-of-Thought, Tree of Thoughts) for scalable and efficient agent systems.

• Develop clean, scalable, and production-ready code in Python.

• Integrate LLMs with traditional systems for hybrid intelligence solutions.

• Apply advanced prompt engineering in collaboration with SMEs to drive accurate, context-aware agent performance.

• Work in a team-first environment, contributing to design sessions, knowledge sharing, and peer reviews.

• Support innovation by staying current with the latest advancements in GenAI and agentic frameworks.