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Investment Management AI Architect - Direct Client

Hybrid in San Francisco, CA, US • Posted 1 day ago • Updated 1 day ago

Contract W2

Able to Sponsor

Hybrid

Depends on Experience

Fitment

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Overview

We are seeking a hands-on AI Architect to design and implement AI-driven solutions across the organization. This role will focus on building intelligent AI agents, integrating LLM and RAG (Retrieval-Augmented Generation) technologies, and establishing scalable AI architecture on Azure to enhance business efficiency and drive data-driven decision-making, including generating investment insights.

Key Responsibilities

Define and lead enterprise AI architecture, strategy, and roadmap across the organization.
Design, build, and deploy AI agents, agentic frameworks, and LLM-based solutions.
Implement RAG-based systems, including knowledge retrieval, vector search, and domain-specific AI models.
Integrate Generative AI into enterprise applications, workflows, and data platforms.
Collaborate with business, data, and engineering teams to identify and prioritize AI use cases.
Re-architect legacy systems to incorporate AI-driven capabilities.
Establish scalable AI infrastructure, governance, and best practices on Azure.
Develop solutions leveraging knowledge graphs and domain-specific data models.
Work with structured and unstructured financial data to generate insights and improve decision-making.
Define KPIs, drive adoption, and lead cross-functional teams to deliver AI initiatives at scale.

Required Skills

10+ years of experience in software engineering, architecture, or enterprise systems.
3+ years of hands-on experience with AI/ML, Generative AI, or LLM-based solutions.
Strong programming skills in Python with frameworks such as PyTorch or TensorFlow.
Experience with LLMs, RAG, AI agents, LangChain, OpenAI APIs, or similar technologies.
Experience building end-to-end AI solutions (from concept to production).
Knowledge of APIs, microservices, data pipelines, and cloud platforms (Azure preferred).
Experience with knowledge graphs, vector databases, and semantic search.
Familiarity with MLOps, model deployment, and real-time inference optimization.
Strong experience working with cross-functional teams and leading large-scale initiatives.
Experience in financial services or the wealth/asset management domain is preferred.

Nice to Have / Preferred

Experience building domain-specific LLMs or post-training models.
Exposure to real-time AI systems and performance optimization.
Prior experience driving measurable business impact (e.g., efficiency gains, revenue growth, automation).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91009931
Position Id: 8954967
Posted 1 day ago

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