Job Description
Seeking an innovative and technically skilled AI Solution Engineer to join our Wealth Management AI Center of Excellence. In this pivotal role, you will design, prototype, and deliver intelligent solutions—leveraging GenAI, LLMs, and agent-based technologies—to transform advisor workflows, client engagement, and operational efficiency.
Key Responsibilities
Opportunity Identification: Collaborate with business teams to identify high-impact use cases for GenAI and agent-based systems that enhance client experience, advisor productivity, and operational efficiency.
Solution Design: Architect and prototype intelligent solutions using large language models (LLMs), retrieval-augmented generation (RAG), and agent orchestration frameworks (e.g., LangChain, LangGraph, AutoGen).
Agent Development & Integration: Build and integrate autonomous agents for multi-step tasks such as financial planning, client onboarding, and investment analysis, connecting with CRM, portfolio, and data platforms.
Technical Implementation: Deploy and maintain GenAI‑powered applications, ensuring performance, security, and compliance with financial regulations.
Stakeholder Collaboration: Work closely with product managers, compliance, and wealth advisors to ensure solutions align with business goals and regulatory standards.
Documentation & Enablement: Develop technical documentation, demos, and training materials to support adoption and scaling of GenAI capabilities across the organization.
Post‑launch Support: Monitor usage data and logs, troubleshoot integration or model‑performance issues, and coordinate escalations with engineering and support teams.
Continuous Improvement: Stay up to date with the latest advancements in AI, LLMs, and agentic frameworks; relay customer insights to product and engineering teams to influence the roadmap.
Compliance & Responsible AI: Implement guardrails, monitoring, and feedback loops to ensure reliable, safe, and compliant agent behavior; contribute to Responsible AI practices and documentation.
Mentorship & Enablement: Run workshops, training sessions, and co‑creation labs to build AI literacy and enable teams to experiment responsibly.
What You Bring
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
3+ years of experience in AI/ML solution design and delivery, preferably in financial services or a regulated industry.
Hands‑on experience with LLMs (Large Language Models), agent frameworks, and AI orchestration tools (e.g., LangChain, AutoGen, Hugging Face).
Strong systems design and solution architecture skills.
Familiarity with cloud platforms (Azure, AWS, GCP), MLOps, and secure application deployment.
Experience with version control (e.g., GitHub) and CI/CD pipelines.
Understanding of AI evaluation metrics, interpretability, ethical AI, and compliance.
Excellent cross‑functional collaboration and communication skills; ability to translate business needs into technical solutions for both technical and non‑technical stakeholders.
Knowledge of financial services, wealth management, or regulatory environments is an asset.
Experience with Agile delivery and rapid prototyping methodologies.
Growth and enablement mindset: passionate about teaching, upskilling teams, and building a culture of responsible AI adoption.
Nice‑to‑Have Skills
Experience with frontend frameworks (React, Angular, Vue) for building user‑facing AI tools.
Familiarity with authentication protocols (OAuth, SAML, JWT, TLS).
Experience with data visualization tools (Tableau, Power BI, matplotlib).
Exposure to prompt engineering and fine‑tuning LLMs.
Experience with containerization (Docker, Kubernetes) and cloud‑native deployment.
Prior work involving SaaS platform integrations or enterprise system integration.
Seniority Level
Mid‑Senior level
Employment Type
Contract
Job Function
Information Technology
Industries
Banking, Investment Banking, and Financial Services
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