AI Developer & Implementation Specialist

abra•Wheaton, IL
•Onsite

About The Position

abra is seeking a AI Developer & Implementation Specialist to join its AI team and lead the development and implementation of advanced AI solutions across the organization’s enterprise systems. The role combines hands-on development, business understanding, solution architecture, and integration with core business systems.

Requirements

  • A minimum of 5 years of hands-on software development experience – mandatory.
  • Hands-on experience with Python development – mandatory.
  • Experience developing LLM-based AI solutions – mandatory.
  • Experience developing AI agents and integrating them with enterprise systems.
  • Experience working with REST APIs and backend services.
  • Familiarity with LangChain, LangGraph, or equivalent frameworks.
  • Experience working with SQL/NoSQL databases.
  • Understanding of system architecture, business processes, and integrations.
  • Ability to work independently, solve problems, and lead development from planning through implementation.
  • Native-level English proficiency – mandatory.

Nice To Haves

  • Experience developing AI solutions in production environments.
  • Experience integrating with Salesforce and ERP systems.
  • Experience working with Snowflake.
  • Experience with Azure/AWS cloud environments.
  • Familiarity with Docker, Kubernetes, and CI/CD pipelines.
  • Experience developing AI systems involving transcription, conversation analytics, and document processing.
  • Experience working in large, complex organizations with multiple interconnected systems.

Responsibilities

  • Develop and implement end-to-end AI solutions, from understanding business needs to production deployment.
  • Develop intelligent AI agents and automate business processes.
  • Build LLM-based solutions, including RAG, prompt engineering, and agent orchestration.
  • Develop API-based integrations with enterprise systems such as Salesforce, ERP systems, and databases.
  • Work with structured and unstructured data, documents, and enterprise information sources.
  • Design and develop backend services that support AI solutions.
  • Perform testing, monitoring, optimization, and performance improvements.
  • Collaborate closely with business stakeholders, development teams, infrastructure teams, information security teams, and external vendors.
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