- Company Name
- Connor, Clark & Lunn Financial Group (CC&L)
- Job Title
- AI Solutions Engineer
- Job Description
-
**Job Title:** AI Solutions Engineer
**Role Summary:**
Technical lead responsible for designing, prototyping, and operationalizing AI solutions while establishing frameworks, best practices, and toolkits that enable responsible, scalable AI adoption across the organization. Acts as a trusted advisor to business and technology stakeholders, driving AI literacy and ensuring enterprise‑grade implementation.
**Expectations:**
- Deliver end‑to‑end AI solutions that meet business objectives.
- Champion responsible AI practices, compliance, and governance.
- Enable and upskill cross‑functional teams in AI usage.
- Maintain production‑ready AI architecture with robust monitoring and CI/CD.
**Key Responsibilities:**
- Rapidly design and iterate prototypes using LLMs, embeddings, RAG pipelines, and agentic frameworks (e.g., LangChain, AutoGen).
- Translate complex business problems into AI‑enabled workflows and decision‑support tools.
- Build modular, reusable components (prompts, agents, connectors, evaluation harnesses).
- Develop, operationalize, and monitor AI agents for workflow automation and decision orchestration, implementing guardrails and human‑in‑the‑loop controls.
- Partner with business SMEs, data engineers, and governance leads to co‑create compliant, impactful solutions.
- Conduct workshops, training sessions, and labs to raise AI literacy and promote responsible experimentation.
- Deploy models securely on Azure, AWS, or OpenAI APIs; establish CI/CD pipelines, monitoring, rollback procedures, and comprehensive documentation.
- Continuously evaluate emerging AI tools, frameworks, and platforms to advance organizational AI maturity.
**Required Skills:**
- Hands‑on experience with large language models, embeddings, Retrieval‑Augmented Generation (RAG), and generative AI workflows.
- Proficiency in agentic AI frameworks such as LangChain, AutoGen, Hugging Face, or equivalents.
- Expertise with cloud AI services (Azure OpenAI, Azure ML, AWS Bedrock, OpenAI API).
- Strong knowledge of AI evaluation metrics, interpretability, ethical AI, and regulatory compliance.
- Ability to translate business requirements into technical AI solutions and communicate effectively with both technical and non‑technical audiences.
- Demonstrated enablement mindset: teaching, mentoring, and fostering a culture of responsible AI adoption.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related quantitative field (master’s degree preferred).
- Relevant certifications (e.g., Microsoft Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, or similar) are advantageous.