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Senior Gen AI Developer (LLM)
LinkedIn Recruiter Post
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AI Solution Engineer – (GenAI, LLMs)
Posted via LinkedIn Recruiter (not a company profile)
Posted 2 weeks ago
About the role
- Design and implement AI-powered applications for wealth management using GenAI and LLMs, collaborating with business teams to enhance client engagement and operational efficiency.
Responsibilities
- Collaborate with business teams to identify high-impact use cases for GenAI and agent-based systems that improve client experience and advisor productivity. Architect and prototype intelligent solutions utilizing large language models (LLMs), retrieval-augmented generation (RAG), and agent orchestration frameworks like LangChain, LangGraph, and AutoGen. 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. Deploy, monitor, and maintain GenAI-powered applications, ensuring performance, security, and compliance with financial regulations. Work closely with product managers, compliance teams, and wealth advisors to align solutions with business objectives and regulatory standards. Develop comprehensive technical documentation, demonstrations, and training materials to support adoption and scaling across the organization. Provide post-launch support by monitoring system performance, troubleshooting issues, and escalating technical challenges as needed. Stay current with advancements in AI, LLMs, and agent frameworks; communicate insights to influence product and engineering roadmaps. Implement guardrails, monitoring, and feedback mechanisms to ensure responsible, safe, and compliant AI behavior; contribute to Responsible AI practices. Lead workshops, training sessions, and co-creation initiatives to foster AI literacy and responsible experimentation within teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 3+ years of experience in AI/ML solution design and deployment, preferably within financial services or regulated industries. Hands-on experience with LLMs, agent frameworks, and orchestration tools (e.g., LangChain, AutoGen, Hugging Face). Strong systems design and solution architecture skills. Proficiency with cloud platforms (Azure, AWS, GCP), MLOps, and secure deployment practices. Skilled in Python and/or JavaScript; experience with REST APIs and integration patterns. Familiarity with version control systems (e.g., GitHub) and CI/CD pipelines. Knowledge of AI evaluation, interpretability, ethical AI principles, and regulatory compliance. Excellent communication and collaboration skills for cross-functional teams. Understanding of financial services and wealth management environments is an asset. Experience with Agile methodologies and rapid prototyping. Growth mindset with a passion for teaching and building responsible AI capabilities.
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