Enterprise Architect
Atos
full-time
Posted on:
Location Type: Office
Location: Windsor • 🇨🇦 Canada
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudETLGoogle Cloud PlatformKubernetesMicroservicesPythonPyTorchTensorflow
About the role
- Design and implement agentic architectures (single- and multi-agent systems)
- Fine-tune and adapt models (LoRA, RAG, prompt optimization)
- Build autonomous workflows including task decomposition and planning
- Collaborate with cross-functional teams for agent design and implementation
Requirements
- Strong understanding of LLMs, multimodal models, and transformer architectures
- Experience with fine-tuning/adapting models (LoRA, RAG, prompt optimization, RLHF basics)
- Ability to design and implement agentic architectures (single- and multi-agent systems)
- Hands-on experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, Swarm)
- Skill in defining agent roles, capabilities, tools, and memory patterns
- Experience building autonomous workflows: task decomposition, planning, and self-correction loops
- Strong prompt engineering skills (system prompts, dynamic context building, tool-calling protocols)
- Knowledge of grounding strategies to reduce hallucinations and enforce business rules
- Proficiency in Python and common AI/ML libraries (PyTorch, TensorFlow, OpenAI/Anthropic SDKs)
- Experience building and consuming APIs and microservices for agent tool use
- Familiarity with event-driven and asynchronous programming patterns
- Experience with RAG pipelines (embeddings, vector stores, retrieval optimization)
- Knowledge of data engineering fundamentals (ETL, data quality, schema design for knowledge bases)
- Deep experience with cloud platforms (Azure, AWS, GCP) for AI workloads, including:
- Model hosting and inference optimization
- Serverless and container-based architectures
- Cost monitoring and scaling strategies
- Proficiency in cloud-native deployment architectures (Kubernetes, service meshes, managed inference endpoints)
- Experience deploying agentic systems within GitHub Enterprise environments, including:
- CI/CD pipelines using GitHub Actions
- Secure secrets management and environment configuration
- Workflow automation and guardrail integration
- Compliance with enterprise governance and code review standards
- Ability to instrument and monitor agent behavior (telemetry, tracing, logs, cost and latency tracking)
- Experience defining and running evaluations for agents (task success, reliability, safety metrics)
- Understanding of security, privacy, and responsible AI principles (PII handling, access controls, auditability)
- Strong debugging and troubleshooting skills for complex, tool-using agent workflows
- Ability to collaborate with product, data, and engineering teams to translate business needs into agentic solutions
- Clear communication skills for documenting agent designs, assumptions, limitations, and guardrails.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
agentic architecturesfine-tuning modelsprompt optimizationtask decompositionPythonPyTorchTensorFlowRAG pipelinescloud-native deployment architecturesdebugging and troubleshooting
Soft skills
collaborationclear communicationproblem-solvingability to translate business needsstrong understanding of security and privacy principles