Staff Agentic AI Engineer
New
J
JobgetherEnterprise AI
CanadaFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 5–7+ years of experience in AI/ML engineering, applied machine learning, NLP, or AI systems development.
- Required Skills
- AWSPythonMachine LearningNLPLLMLangChain
Requirements
- Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, or related quantitative discipline.
- 5–7+ years of experience in AI/ML engineering, applied machine learning, NLP, or AI systems development.
- 2+ years of hands-on experience building production LLM applications or AI agent systems.
- Proven experience developing AI agents used by customers, enterprises, or business users.
- Experience with agent orchestration frameworks such as LangGraph or LangChain.
- Strong Python engineering skills with experience building scalable production software.
- Experience designing AI architectures involving reasoning flows, tool use, memory, retrieval, and guardrails.
- Strong understanding of RAG architectures, embeddings, retrieval optimization, and knowledge-grounded generation.
- Experience creating AI evaluation systems, including quality metrics, automated testing, and production monitoring.
- Experience deploying and operating AI systems in AWS cloud environments.
- Familiarity with AI-assisted development tools such as Codex, Claude Code, or Cursor.
- Ability to work independently, demonstrate strong technical judgment, and lead complex engineering initiatives.
Responsibilities
- Design and optimize production-grade AI agent systems that power enterprise automation workflows.
- Architect agent workflows incorporating reasoning, tool usage, retrieval, guardrails, and performance monitoring.
- Evaluate and implement emerging agent orchestration frameworks and patterns.
- Develop and maintain AI evaluation frameworks, including LLM-as-judge workflows and regression testing.
- Diagnose and improve agent performance by analyzing prompts, retrieval quality, and latency.
- Build RAG and embedding-based solutions for intelligent access to enterprise knowledge.
- Develop scalable Python services and AI platform components in cloud environments.
- Design systems that transform unstructured information into structured knowledge models.
- Collaborate with cross-functional teams to translate AI innovations into practical features.
- Establish engineering standards and best practices for optimizing agentic AI systems.
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