CapIntel
wealth management
ContextEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Context Engineer at CapIntel. Skills: LLM integration, agentic workflows, production reliability, RAG pipelines, context management, AI feature development. Design and implement LLM-powered features into our core application via model APIs. Architect and maintain retrieval-augmented generation (RAG) pipelines”
What You'll Achieve.
make our AI features reliable, accurate, and scalable; directly enhance the advisor and client experience; deliver great work
Industry & Context.
problem-solving instincts
What They're Looking For.
Must Have
5+ years of professional software engineering experience, at least 1–2 years working with LLMs in a production context, experience with Python or Node and building API-integrated backend services, Hands-on experience with an orchestration or execution framework, Working knowledge of RAG architecture, Working knowledge of vector databases (e.g. Pinecone, pgVector, AWS OpenSearch), Working knowledge of semantic search, Experience building or consuming REST APIs, Experience integrating with third-party services
Nice to Have
Experience with the Model Context Protocol (MCP) or similar tool-integration standards, Familiarity with LLMOps practices: tracing, observability (e.g. LangSmith, Datadog), and model versioning, Exposure to multi-agent architectures and orchestration patterns, Knowledge of AI output validation, context safety, and governance considerations particularly relevant in regulated industries like financial services, Familiarity with AWS or cloud-based infrastructure, Familiarity with containerised deployments (Docker, Kubernetes)
What You'll Do.
Design and implement LLM-powered features into our core application via model APIs
Architect and maintain retrieval-augmented generation (RAG) pipelines
Manage context window strategy
Design and implement agentic workflows enabling the platform to handle multi-step
Build guardrail and output validation layers
Develop reusable agent primitives
and workflow components
Build evaluation frameworks to measure context effectiveness
and agent reliability in production
Monitor deployed AI systems for failure patterns and implement mitigation strategies
Translate business requirements
and proof of concepts into production AI system specifications
How You'll Work.
Team & Collaboration
embedded in development teams working closely with engineers, product managers, and domain experts across the organization; Collaborate with Product, Product Engineering, Implementation, and Data teams; Comfortable collaborating with cross-functional teams in a fast-paced, high-growth environment; Ability to communicate technical concepts clearly to both technical and non-technical partners
Communication Scope
Ability to communicate technical concepts clearly to both technical and non-technical partners
Full Job Description
CapIntel is a software platform built for wealth management enterprises to help financial advisors explain complex investment strategies to their clients. Advisors at some of the biggest banks across North America are winning trust by using CapIntel to easily compare investments and create compelling, educational presentations. Ultimately, we're focused on investors getting better service, understanding their investments, and feeling at ease knowing their future is secure. Since launching in 2019, CapIntel has seen rapid adoption and industry recognition, earning top placements in Deloitte’s Technology Fast 50 Canada and Fast 500 North America in 2025, ranking us among the fastest-growing technology companies. To support this momentum, we’re growing our team rapidly—investing in people who drive innovation at scale to expand our impact across the North American wealth management industry. About the Role As a Context Engineer at CapIntel, you'll sit at the intersection of AI infrastructure and engineering. You will be responsible for how large language models are integrated into our core platform and how our engineering team adopts agentic workflows. This is a hands-on, production-focused role, not a research one. You'll build the systems that make our AI features reliable, accurate, and scalable for the wealth management enterprises that depend on us. You'll be embedded in development teams working closely with engineers, product managers, and domain experts across the organization to design and deliver LLM-powered capabilities that directly enhance the advisor and client experience. As one of the first practitioners in this discipline at CapIntel, you'll also help define what context engineering looks like here: setting patterns and practices the broader team can build on. This role is ideal for someone who thinks in systems, cares about production reliability over demo-day performance, and is energized by working in a discipline that is evolving quickly. What You'
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