GenAI Developer

CGI Group Inc.•Reston, VA

41d•Hybrid

About The Position

CGI has an immediate need for a GenAI Developer to join our team. This is an exciting opportunity to work in a fast-paced team environment supporting one of the largest customers. We take an innovative approach to supporting our client, working side-by-side in an agile environment using emerging technologies. 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 Reston, VA. A hybrid working model is acceptable. We are seeking a skilled and experienced Generative AI Developer to join our team on a contract basis in Plano, Texas. This role is ideal for a mid to senior-level professional with a strong background in software engineering and hands-on experience in AI/ML, particularly in the financial or legal domain. You will be responsible for designing and refining prompts for large language models (LLMs), developing data pipelines, and deploying AI solutions that enhance financial reporting and client communication tools. This is a collaborative role that requires both technical expertise and the ability to align AI solutions with business goals.

Requirements

8+ years of experience in software engineering, ideally with exposure to financial or legal systems.
2-3 years of hands-on experience in AI/ML roles, including prompt engineering for LLMs.
Proficient in Python and SQL for data analysis and manipulation.
Strong experience with AWS services, especially SageMaker, S3, Redshift, and Lambda.
Solid understanding of financial data, KPIs, and reporting standards.
Experience building and maintaining ETL workflows and data pipelines.
Familiarity with LLMs such as Anthropic Claude or Sonnet.
Ability to collaborate effectively with cross-functional teams including data scientists and business stakeholders.
Excellent written and verbal communication skills.

Nice To Haves

Experience with vector databases like FAISS or Pinecone.
Knowledge of retrieval-augmented generation (RAG) techniques.
Exposure to data visualization tools such as Power BI or Tableau.
Understanding of MLOps practices and model lifecycle management.

Responsibilities

Designing and refining prompts for large language models (LLMs)
Developing data pipelines
Deploying AI solutions that enhance financial reporting and client communication tools