Staff AI Engineer
TELUS Digital
full-time
Posted on:
Location Type: Remote
Location: Brazil
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Job Level
About the role
- Integrate Generative AI models, such as LLMs, with external APIs, tools, and databases using secure and efficient orchestration patterns.
- Design, develop, and deploy AI workflows and Agentic AI solutions, enabling the seamless orchestration of intelligent agents to plan and perform tasks while leveraging autonomous and/or human-in-the-loop paradigms.
- Implement and optimize multi-agent systems, leveraging standards and protocols such as Model Context Protocol (MCP), and emerging frameworks for agent interoperability and access to external resources.
- Develop evaluation frameworks, metrics, and checkpoints for agent autonomy, performance, and safety, ensuring compliance with moderation, security, and ethical standards.
- Evaluate, analyse, and gather insights out of structured and non-structure data leveraging Generative AI models and pipelines.
- Ensure robust AI agent operations by applying observability, monitoring, and MLOps best practices, facilitating reliable deployment pipelines and continuous performance optimization.
- Orchestrate AI model selection, tuning, and performance validation to meet specific agent-based application needs.
- Communicate complex AI concepts, systems, and decisions effectively to technical and non-technical stakeholders, promoting transparency and trust in AI delivery.
- Foster an environment of innovation and collaboration, engaging and encouraging teams to solve complex problems and share ideas that drive innovative approaches.
Requirements
- Proven experience designing and deploying AI architectures, with expertise in Generative AI, NLP, LLM integration, and software engineering.
- Strong background in building software platforms (Python/Django, Java/Spring, TypeScript/Express, etc.) capable of API integration and orchestration.
- Strong understanding of the trade-offs between various generative AI models and the ability to choose the right model for specific use cases.
- Hands-on experience with function-calling and tools integration into LLM models, leveraging frameworks such as Model Context Protocol (MCP).
- Experience with Agentic AI orchestration frameworks such as LangGraph, Google ADK, OpenAI Agents SDK, CrewAI, or others.
- Expertise in data embeddings, vector databases, and chunking strategies, understanding the trade-off between different options, and leveraging it to optimize data ingestion and application performance.
- Experience using CI/CD tools (GitHub Actions, Jenkins, AWS CodeDeploy, Azure Pipelines) to streamline development and deployment workflows.
- Hands-on experience deploying software on leading cloud platforms and utilizing AI tools like AWS Bedrock and Azure AI Services.
- Experience leveraging evaluation frameworks (e.g., RAGAS, OpenAI Eval) and tools (e.g., Arize, LangSmith, Braintrust) to assess business and performance metrics of AI solutions.
- Understanding of performance optimization, including the use of observability platforms, event tracking, and performance validation.
- Practical knowledge of deploying AI solutions using cloud platforms like AWS, Azure, or GCP, utilizing services such as AWS Bedrock or Azure AI Services.
- Excellent skills in prompt and context engineering, ensuring the usage of the right techniques to meet diverse project requirements.
- Ability to communicate complex AI solutions and concepts effectively to technical and non-technical stakeholders.
Benefits
- Health and dental plan
- Life insurance
- Monthly voucher for meals, culture, education, health and mobility
- Child care assistance and more!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Generative AINLPLLM integrationPythonDjangoJavaSpringTypeScriptExpressdata embeddings
Soft Skills
communicationcollaborationproblem-solvinginnovationtransparencytrust