Agentic AI Developer

Pacer Group; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401(k)

Job summary

Pacer Group is seeking an advanced AI software engineer to architect enterprise-grade generative AI and agentic systems. You will bridge legacy financial infrastructure with modern LLM orchestration frameworks to drive automation and intelligent decision-making for clients.

The role reports to the Director of AI within the Advanced Technology and Engineering department, requiring strong experience in Python/Java, microservices, and scalable RESTful APIs.

Qualifications

• Must-have skills include LangChain, LangGraph and LangSmith with Python/Java, microservices and RESTful APIs.
• Experience with data pipelines and cloud-native architectures for LLM-based solutions and orchestration tools.
• Agentic AI capabilities including planning, memory, agent frameworks; Model Context Protocol & ADK.

Responsibilities

• Architect and implement end-to-end LLM-based solutions using LangChain, LangGraph, and Semantic Kernel | Ensuring robust scalability and high performance.
• Develop sophisticated AI systems featuring advanced agentic capabilities including multi-step planning, persistent memory management, and autonomous agent frameworks.
• Build and optimize robust Retrieval-Augmented Generation (RAG) pipelines alongside seamless vector database integrations using Redis for rapid information retrieval.
• Design and execute enterprise system integrations utilizing Model Context Protocol and Agent Development Kits to connect AI agents with core banking platforms.
• Leverage 7 to 8 years of core software engineering experience in Python and Java to develop clean, scalable microservices and high-throughput RESTful APIs.

Skills

LangChain

LangGraph

LangSmith

Python

Java

Microservices

RESTful APIs

Data pipelines

cloud-native architectures

LLM-based solutions

orchestration tools

Agentic AI capabilities

Model Context Protocol

ADK

Enterprise system integration

Tools

Semantic Kernel

Job description

Application Deadline: September 25, 2026

SKILLS REQUIRED

Primary (Must-Have):

• LangChain, LangGraph, LangSmith | Python / Java, microservices, RESTful APIs
• Data pipelines, cloud-native architectures | LLM-based solutions & orchestration tools
• Agentic AI capabilities (planning, memory, agent frameworks) | Model Context Protocol & ADK

Secondary (Good to Have):

• Semantic Kernel | Enterprise system integration

POSITION OVERVIEW

This role sits within the Advanced Technology and Engineering department, reporting directly to the Director of Artificial Intelligence. The incumbent will solve complex scalability and integration bottlenecks by architecting enterprise-grade generative AI and agentic systems, bridging the gap between legacy financial infrastructure and modern LLM orchestration frameworks to drive automation and intelligent decision-making for the client.

ROLES & RESPONSIBILITIES

• Architect and implement end-to-end LLM-based solutions using advanced orchestration frameworks like LangChain, LangGraph, and Semantic Kernel | Ensuring robust scalability and high performance.
• Develop sophisticated AI systems featuring advanced agentic capabilities including multi-step planning, persistent memory management, and autonomous agent frameworks.
• Build and optimize robust Retrieval-Augmented Generation (RAG) pipelines alongside seamless vector database integrations using Redis for rapid information retrieval.
• Design and execute enterprise system integrations utilizing Model Context Protocol and Agent Development Kits to connect AI agents with core banking platforms.
• Leverage 7 to 8 years of core software engineering experience in Python and Java to develop clean, scalable microservices and high-throughput RESTful APIs.

BENEFITS

• Medical | Dental | Vision | 401(k)

EEOC Compliance

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.

DISCLAIMER

AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.