Sr. AI engineers core skills: LLM, RAG, Python, RAIOPs, AI Agent, Azure or AWS, 1-2 years of AI project experience, banking industry working experience pre

Senior AI Engineer / GenAI Developer to support AI-driven initiatives within our Tier1 banking client's Wealth Management technology environment.

Duration: 6 Months

Location: Toronto, Hybrid

The successful candidate will bring hands-on experience designing, building, and deploying AI-enabled solutions using LLMs, RAG frameworks, AI agents, Python, and cloud-native services. This role is ideal for an engineer who has worked on applied AI projects in an enterprise setting and can help move GenAI use cases from concept through build, integration, testing, and production readiness.

Key Responsibilities

• Design, develop, and support AI/GenAI solutions leveraging large language models, retrieval-augmented generation, AI agents, and Python-based services.
• Build and enhance RAG pipelines, including document ingestion, chunking, embedding, vector search, semantic retrieval, prompt orchestration, and response evaluation.
• Develop AI agent workflows to support automation, decision support, operational efficiency, and user-facing or internal banking use cases.
• Work with cloud platforms such as Azure or AWS to deploy, integrate, monitor, and scale AI solutions.
• Collaborate with architecture, data, security, risk, product, and business stakeholders to ensure AI solutions meet enterprise banking standards.
• Support model evaluation, prompt tuning, accuracy testing, guardrail implementation, and responsible AI practices.
• Contribute to RAIOps or AI operations initiatives, including monitoring, reliability, observability, and automation of AI-enabled platforms.
• Integrate AI solutions with enterprise applications, APIs, data platforms, and internal banking systems.
• Participate in Agile delivery ceremonies and provide technical input into solution design, estimation, implementation planning, and production support.

Must Haves:

• Senior-level software engineering experience with strong hands-on development in Python.
• Practical project experience with LLMs, RAG, AI agents, and GenAI application development.
• Minimum 1-2 years of applied AI project experience, ideally within an enterprise or regulated environment.
• Experience building or integrating with cloud-based AI services on Azure or AWS.
• Understanding of RAG architecture, vector databases/search, embeddings, prompt engineering, and model evaluation approaches.
• Experience with RAIOps, AI platform operations, observability, automation, or reliability engineering for AI-enabled systems.
• Ability to work across technical and business teams to translate AI use cases into scalable engineering solutions.
• Strong communication skills and comfort working with stakeholders in a complex banking environment.

Nice to Have:

• Prior experience working in banking, wealth management, capital markets, insurance, or financial services.
• Experience with enterprise AI governance, model risk, data security, privacy, compliance, or responsible AI controls.
• Exposure to Azure OpenAI, AWS Bedrock, Azure AI Search, LangChain, LlamaIndex, FastAPI, vector databases, or similar AI engineering tools.
• Experience deploying AI solutions into production within a secure, enterprise-grade environment.