ironquill.tech/board

$ cat jobs/lead-genai-engineer-inizio-partners-corp-e2cddfa1be6e.json

Lead GenAI Engineer

inizio partners corp·Canada·senior
pythonrestgrpcawsgcpazurellm
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Staff Generative AI Engineer Background We are looking for a Staff Generative AI Engineer to design, build, and ship production-grade Generative AI and Agentic AI applications that delivery business value across the organization. This role is focused on building AI applications and services at scale. You will be responsible for building robust, secure, and highly scalable systems that integrate with leading cloud-based AI services. As a senior individual contributor, you will bring deep technical expertise, drive high-quality engineering practices, and serve as a mentor for junior to mid-level engineers. You will work closely with software engineers, data scientists, and product teams to translate business problems into production-grade AI applications and services. Key Responsibilities Application and Solution Engineering 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 LangChain, LangGraph, 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

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