Design, build, and ship production-grade Generative and Agentic AI applications and services for internal and external users Develop high-quality backend services in Python, with strong software engineering rigor around testing, performance, and maintainability Champion reusability and abstraction in everything you build by designing and building modular, well-abstracted components and libraries Build multi-agent systems using frameworks such as Lang

Chain, Lang

Graph, Claude Agent SDK and Google ADK Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking Build clean, well-tested RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services Contribute to platform architecture decisions and engineering best practices Take applications from prototype through production deployment, hardening, and ongoing operation Mentorship and Team Development Mentor and coach junior and mid-level engineers through code reviews, architecture discussions, and pair programming Foster a culture of engineering excellence, knowledge sharing, and continuous improvement Participate in technical design reviews and contribute to the professional growth of team members What you must have:



10-15 years of professional software engineering experience with at least 3-5 years of experience building AI/ML software products Bachelors degree in Computer Science or a related field (Masters degree preferred) Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance) Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock Experience with agent frameworks (e.g., Lang

Chain, Lang

Graph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB) Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure Robust understanding of API design, distributed systems, and cloud-native architecture Proven track record of taking systems from design through production deployment and operation Nice to have: Experience with containerization and orchestration (Docker, Kubernetes) Knowledge of Generative AI Risk Management frameworks (NIST RFM) Experience supporting developer platforms or internal tooling Experience writing design documents or helping define engineering standards Salary/Rate Range : $155,000-$165,000 Thank you for your interest in this opportunity.

If you are selected to move forward in the process, we will contact you directly.

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📌 Staff AI Engineer (Toronto)
🏢 TEEMA
📍 Toronto