AWS Agentic AI Developer

Position Description:

** Extensive hands-on development experience in Agentic AI projects on AWS native services is required**

** This role is flexible within proximity to a CGI office in Toronto to accommodate a hybrid work model**

The Emerging Technologies team in Global Technology and Operations (GTO) Canada at CGI is a trusted Data, Cloud and AI advisor and go-to implementation partner for our global clients' Data and Advanced Analytics needs. We're an entrepreneurial team that is on a continuous mission to position CGI as the best-in-class AI partner and develop new and exciting opportunities in latest technologies. Our capabilities in Agentic AI are constantly evolving with current focus being on AI agents governance and mitigating risks associated with Agentic AI.
Are you an Agentic AI candidate that has not just played around with Large Language Models, Copilots and Coding Assistants but also has experience building hands on multi-agent orchestration based Agentic AI solutions.
Working with us, you will be supported by our best and brightest AI Scientists and Architects working on challenging projects in Agentic AI.

Your future duties and responsibilities:

As an Agentic AI Developer on this team your responsibilities will include:
. Serve as an Intermediate AI/ML Engineer for agent-based initiatives, including scoping, estimation, and initial architectural design of AI & Business Applications.
. Design, develop, and deploy intelligent agents using AWS Bedrock, LangChain, Kiro, Graph DB, Strands, and related agent frameworks.
. Build and maintain applications using AWS agent core framework, orchestration layers, and hierarchical agent workflows to support complex reasoning and automation
Develop secure, scalable APIs using AWS Lambda and API Gateway to expose AI and agent capabilities to downstream systems.
. Implement prompt engineering best practices to optimize model performance, accuracy, and reliability across use cases.
. Design and implement RAG (Retrieval Augmented Generation) pipelines leveraging vector databases and knowledge graphs.
. Monitor, evaluate, and optimize LLM performance, cost, latency, and reliability in production environments.
. Support testing cycles by validating AI outputs, identifying gaps, and improving agent behavior through tuning and iteration.
. Ensure solutions meet enterprise standards for security, compliance, and responsible AI usage
This role comes with sometimes intense delivery expectations churning out POVs for clients in a short period of time and then going on to implement a full-scale production solution ensuring right user experience and adoption

Required qualifications to be successful in this role:

. Hands-on work experience with implementing Agentic AI business process automation workflows in at least 1-2 different projects
Strong experience with Python & Spark for building AI, data, and agent-based applications.
. Hands-on experience with AWS Bedrock and large language models (LLMs).
. Experience using LangChain, Strands, or similar agent frameworks.
. Strong understanding of agent core design, multi-agent systems, and orchestration patterns.
. Experience building serverless solutions using AWS Lambda and API Gateway.
. Solid knowledge of prompt & context engineering techniques and LLM optimization strategies.
. Experience integrating LLMs with enterprise systems via APIs.
. Build Solutions to any complex business problem using AI-Development Life Cycle methodology.
. Strong problem-solving, communication, and collaboration skills.
Preferred qualifications:
. Experience with broader AI and agent frameworks, including hierarchical agents and autonomous agent architectures.
. Familiarity with Model Context Protocol (MCP) and emerging agent interoperability standards.
. Experience with Kiro or similar AI IDE tools for agent-assisted development workflows.
. Experience with CI/CD pipelines, Infrastructure as Code (CDK, CloudFormation, or Terraform), and version control (Git).
. Familiarity with containerization technologies such as Docker, Amazon ECS, or EKS for production AI deployments.
. Experience with AWS Quick Tools and AWS Frontier Agents.
. Hands-on experience with deep research agents and multi-step reasoning workflows.
. Experience implementing RAG using Vector Databases (e.g., OpenSearch, Pinecone, FAISS) and Graph Databases.
. Exposure to model tuning, embeddings, and evaluation techniques.
. Knowledge of enterprise AI governance, security, and responsible AI practices.

CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes various factors including but not limited to skill set level, geographic market, experience and training, and licenses and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $80, - $,. This role is an existing vacancy.

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Skills:

• Agentic AI
• Data Engineering
• Data Engineering
• Data Migration
• Data Modeling
• Data Validation
• Data Warehousing
• English