We9re hiring an
AI Solution Engineer in our AI Solutions engineering team. You build the AI systems that Connor, Clark & Lunn Financial Group and our affiliate teams use in day-to-day work. You turn
signed-off specifications into
production-ready AI assistants, agents, and workflow automations. You own build quality, reliability, safety, traceability, and maintainability, and partner closely with Data Engineering and MLOps to ship responsibly in a regulated financial services environment. We operate on a hybrid model with three days a week in-office to facilitate team collaboration.
What You Will Do- Build AI assistants and agents end-to-end from a signed-off spec, retrieval, tool integrations, prompt logic, source citation, and workflow integration
- Design and maintain retrieval pipelines, chunking strategy, metadata schema, indexing, access controls, and query optimization
- Engineer prompts with discipline, write, test, evaluate, and iterate; document failure modes and edge cases
- Own code quality and handoff, version artifacts, write tests where appropriate, and maintain clean, reviewable documentation
- Partner with Data Engineering to make data retrieval-ready, define ingestion needs, document assumptions, and validate data quality impacts
- Deploy through standard MLOps pipelines, monitoring/alerting, rollback readiness, cost controls, and operational runbooks
- Collaborate with affiliate teams during builds, demo real increments, capture feedback, and incorporate changes without breaking scope
- Document known limitations, risks, and mitigations before UAT, set expectations and prevent surprises for business stakeholders
What You Will Bring - Strong Python skills with experience shipping LLM applications end-to-end (build, test, deploy, and operate)
- Hands-on RAG experience, document processing, vector databases/search, and retrieval evaluation (precision/recall, grounding quality)
- Experience with agent frameworks (e.g., LangChain, LlamaIndex or equivalents), including tool use, orchestration, and multi-step flows
- Experience on enterprise AI platforms (e.g., Azure OpenAI, Google Vertex AI, Anthropic APIs), including security and cost/performance trade-offs
- Prompt engineering fundamentals, structured prompting, output constraints, adversarial/failure-mode testing, and reproducibility
- Comfort working with semi-structured/unstructured data (PDFs, financial docs, emails, notes) and translating it into retrieval-ready assets
- Delivery mindset and strong written communication, hold scope, write clear technical documentation, and finish to production-quality
The salary range for this position is $125,000 - $145,000. The salary range provided reflects the base salary range for this position as required by legislation. In addition, there is an annual performance bonus which contributes to the total compensation for this position. Further questions may be directed to the HR team during the interview process.
#LI-Hybrid #LI-KC1
For a closer look at how you can build your career with us, we invite you to explore cclgroup.com.
