Aviva Canada
Insurance
SeniorGenAIEngineer
Neural analysis suggests this role is
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“Senior GenAI Engineer at Aviva Canada. Skills: Generative AI, Agentic AI, Enterprise LLM platforms, RAG pipelines. Design and implement enterprise Generative AI services. Build retrieval-augmented generation (RAG) pipelines”
Industry & Context.
What They're Looking For.
Must Have
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or equivalent, 6+ years of experience in Software engineering, AI engineering, or data platform development, Experience designing and delivering enterprise Generative AI applications, Hands-on experience with enterprise data and ML platforms such as Snowflake or Databricks, Experience building cloud-native solutions on AWS, Azure or Google Cloud, Python programming skills, Experience building RAG pipelines, semantic search and AI driven workflows, Experience integrating AI with APIs, enterprise applications, and business processes, Ability to design scalable AI architectures with governance, security ad privacy, Experience working with structured and unstructured enterprise data, Practical experience with containerization technologies, including Docker
Nice to Have
Experience working in insurance or financial services, with exposure to regulated environments, Familiarity with insurance domains such as claims, underwriting, and policy servicing, Experience using enterprise LLM platforms such as Azure OpenAI Service or Amazon Bedrock, Hands-on experience building enterprise knowledge copilots or AI assistants, Experience implementing AI observability and evaluation frameworks, Familiarity with running and optimizing local LLMs, including model tuning, GPU configuration, or on‑device inference
What You'll Do.
Design and implement enterprise Generative AI services
Build retrieval-augmented generation (RAG) pipelines
Implement enterprise semantic search
Develop reusable frameworks for prompt management
Design and deploy AI agents
Implement multi-agent orchestration architectures
Enable AI agents to interact with internal APIs
Integrate AI systems with enterprise data platforms
Implement AI guardrails
Design human-in-the-loop review workflows
Ensure compliance with privacy
Monitor AI and agent outputs
Provide technical leadership in GenAI adoption
Partner with enterprise architecture teams
Help scale GenAI adoption
How You'll Work.
Team & Collaboration
Collaborate with engineering, data, architecture, and business teams; Partner with enterprise architecture and data teams
Full Job Description
## **Experience Aviva** **Together, we are Aviva.** Our values — Care, Commitment, Community, and Confidence — guide how we show up for each other and for our customers. Individually, they’re words. Together, they define who we are. At**Aviva Canada** , we put people first, our employees, our customers, and our communities. We’re proud of a culture built on care, inclusion, and collaboration, where your voice matters and your growth is supported. We’re not just about insurance; we’re about making a real difference by protecting what matters most. ## **The Opportunity** Aviva Canada is building the next generation of AI-enabled insurance platforms and is seeking a Senior GenAI Engineer to own the development of enterprise-grade Generative AI and Agentic AI solutions. This position is dedicated to creating smart AI copilots and autonomous agents that enhance business processes by using enterprise data platforms like Snowflake and current cloud and on-prem technologies. The role emphasizes building robust AI services on enterprise LLM platforms, with a focus on data integration, AI orchestration, agent frameworks, and scalable deployment in the cloud. You will collaborate with engineering, data, architecture, and business teams to deliver secure, compliant, and scalable AI solutions for a regulated insurance environment. ## **What you****’****ll do:** * Design and implement enterprise Generative AI services and knowledge copilots. * Build retrieval‑augmented generation (RAG) pipelines leveraging enterprise data. * Implement enterprise semantic search, knowledge indexing, and document intelligence systems. * Develop reusable frameworks for enterprise prompt management, evaluation, and AI observability. * Design and deploy AI agents capable of planning and executing multi‑step workflows across enterprise systems. * Implement multi‑agent orchestration architectures where specialized agents collaborate to complete business tasks. * Enable AI agents to interact with interna
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