GenAI Engineer

System One Holdings, LLC

• $110K — $130K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in context engineering with enterprise data and semantic search.
  • Proficiency in spec-driven development with a focus on AI-assisted software practices.
  • Strong Python development skills with experience in APIs and CI/CD.
  • Experience deploying applications in AWS/cloud native environments.
  • Hands-on experience with Generative AI and LLM applications including prompt engineering.
  • Experience building AI agents with orchestration and tool integration capabilities.
  • Familiarity with production AI practices including monitoring and performance optimization.

Responsibilities

  • Develop and support production-ready AI applications within a large-scale financial services environment.
  • Translate structured business requirements and acceptance criteria into reliable AI solutions.
  • Integrate AI capabilities with enterprise systems while adhering to security and governance protocols.
  • Implement and enhance features involving semantic search and retrieval augmented generation (RAG).
  • Collaborate on building multi-agent workflows and orchestration for AI agents.
  • Monitor application performance and ensure compliance with Responsible AI practices.
  • Engage with stakeholders to align AI solutions with business objectives and outcomes.

Benefits

  • Hybrid work model (3 days onsite, 2 days remote).
  • Opportunity to work in a large-scale financial services environment.
  • Access to cutting-edge AI technologies and cloud resources.
  • Focus on professional development through hands-on project involvement.
Full Job Description
Job Title: GenAI Engineer
Duration: Full Time / Permanent Position
Location: Lafayette, LA, Knoxville, TN, Columbia, SC, Birmingham, AL

Work Mode: Hybrid (3 Days Onsite - 2 Days Remote)

Position Description
Systemone is seeking an AI Agent Engineer to build and support production ready AI applications and agent based solutions within a large scale financial services environment. This role focuses on developing AI capabilities that combine trusted enterprise data, large language models (LLMs), semantic search, retrieval augmented generation (RAG), and workflow/tool integrations.

The engineer will work from structured requirements and acceptance criteria to develop reliable AI solutions that integrate with enterprise systems and operate within established security, governance, and compliance controls. The role requires strong hands on engineering skills and the ability to translate business needs into practical, measurable AI capabilities.
Experience working in AWS based cloud environments and with enterprise grade AI applications is highly valuable.

Required qualifications to be successful in this role
. 5+ years of experience with context engineering, including enterprise data, semantic search, metadata, knowledge retrieval, and data lineage.
. Experience working with spec driven development, structured requirements, acceptance criteria, and AI assisted software development practices.
. Strong hands-on Python development skills, including APIs, Git, automated testing, and CI/CD.
. Experience developing production applications in AWS/cloud native environments.
. Hands on experience building Generative AI and LLM applications, including prompt engineering, structured outputs, tool/function calling, and RAG.
. Experience developing AI agents, including single agent or multi agent workflows, orchestration, tool integration, memory, and controlled autonomy.
. Experience with production AI practices such as evaluation, observability, monitoring, prompt/version management, performance optimization, and production support.
. Experience integrating applications with enterprise systems using REST APIs, event driven patterns, workflow platforms, and authentication/security controls.
. Understanding of Responsible AI and AI governance, including guardrails, human in the loop processes, security, privacy, auditability, and compliance.
. Ability to translate business requirements into production ready AI capabilities while considering technical trade offs, governance, user experience, and measurable outcomes.
. Financial services or other highly regulated industry experience is a strong plus.

Education:
Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.

Ref: #404-IT Pittsburgh

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