GenAI Engineer

CGI•Lafayette, LA

1d•Hybrid

About The Position

CGI 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. We partner with 15 of the top 20 banks globally, and our top 10 banking clients have worked with us for an average of 26 years!. This role is located at a client site in either Birmingham, AL, Knoxville, TN, Columbia, SC or Lafayette, LA. A hybrid working model is acceptable.

Requirements

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

Nice To Haves

Financial services or other highly regulated industry experience is a strong plus.
Experience working in AWS based cloud environments and with enterprise grade AI applications is highly valuable.

Responsibilities

Build and support production ready AI applications and agent-based solutions within a large-scale financial services environment.
Develop AI capabilities that combine trusted enterprise data, large language models (LLMs), semantic search, retrieval augmented generation (RAG), and workflow/tool integrations.
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.
Translate business needs into practical, measurable AI capabilities.