AI Solution Architect - Capital Markets/LLM/Generative AI/RAG

Overview

Remote
$70 - $80
Contract - Independent
Contract - W2

Skills

Gen AI
LLM
RAG
Capital Markets
Snowflake
Databricks

Job Details

AI Solution Architect

Required Location: Hybrid/Midtown New York City or 100% Remote

Duration: 12+Months

Interview Required: Video

A senior AI Solution Architect with extensive/recent experience working in Trading/Capital Markets with Generative AI and LLM. Candidates need to have experience Architecting end-to-end AI solutions that leverage foundation models (OpenAI, Anthropic), integrating with enterprise data in Snowflake and Databricks. As well as translate business objectives into functional and technical AI/ML solution designs, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning strategies, and safety/guardrails. Candidates must Design and oversee implementation of scalable AI services, pipelines, APIs, and integration points into Capital Markets systems and Ensure solutions adhere to internal security, compliance, and regulatory frameworks, particularly around explainability, bias, and model governance.

  1. How many years working with: AI Solution Architect
  2. How many years working with: Capital Markets
  3. How many years working with: Generative AI and LLM
  4. How many years working with: Snowflake and Databricks
  5. How many years working with: internal security, compliance, and regulatory frameworks
  6. How many years working with: retrieval-augmented generation (RAG), fine-tuning strategies, and safety/guardrails

Job Description: We are seeking a highly skilled AI Solution Architect with Capital Markets experience to lead the design and delivery of next-generation AI solutions leveraging foundation models from OpenAI and Anthropic. This role is pivotal in bridging business domain needs with advanced GenAI technologies. The architect will collaborate with front-office and operations teams to identify high-impact use cases, and then lead the technical design and implementation efforts alongside engineering and data platform teams. A strong understanding of Capital Markets workflows, AI/ML (especially GenAI), and experience working with centralized data platforms like Snowflake and Databricks is essential.

Key Responsibilities:

  • Partner with business units (e.g., trading, research, compliance, operations) to identify and qualify GenAI use cases aligned with business priorities.
  • Architect end-to-end AI solutions that leverage foundation models (OpenAI, Anthropic), integrating with enterprise data in Snowflake and Databricks.
  • Translate business objectives into functional and technical AI/ML solution designs, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning strategies, and safety/guardrails.
  • Design and oversee implementation of scalable AI services, pipelines, APIs, and integration points into Capital Markets systems.
  • Collaborate closely with data engineering teams to ensure data readiness semantic tagging, governance, and accessibility for AI consumption.
  • Provide technical leadership throughout the model lifecycle: use-case evaluation, solution architecture, implementation, validation, and monitoring.
  • Ensure solutions adhere to internal security, compliance, and regulatory frameworks, particularly around explainability, bias, and model governance.
  • Stay current with the AI ecosystem, including emerging capabilities from OpenAI, Anthropic, and open-source alternatives.
  • Mentor engineers and analysts on GenAI best practices and scalable solution patterns.

Required Qualifications:

  • 5+ years of experience in AI/ML solution architecture, with a strong focus on Generative AI and LLMs.
  • 3+ years of Capital Markets domain experience (e.g., fixed income, equities, derivatives, asset servicing, risk, compliance).
  • Demonstrated experience architecting solutions with OpenAI, Anthropic, or other LLM platforms (e.g., Azure OpenAI, Claude, HuggingFace).
  • Strong familiarity with RAG, embeddings, prompt design, fine-tuning, and LLMOps practices.
  • Hands-on experience with Snowflake, Databricks, and modern data architectures.
  • Solid understanding of data governance, lineage, tagging, and access control in regulated environments.
  • Excellent stakeholder management skills; able to communicate complex technical concepts to non-technical business users.
  • Familiarity with model risk management, compliance requirements (e.g., FINRA, SEC, EU AI Act), and ethical AI principles.

Preferred Qualifications:

  • Experience deploying GenAI use cases in financial institutions (e.g., AI-powered research assistants, compliance review automation, trader productivity tools).
  • Knowledge of cloud platforms (Azure, AWS, or Google Cloud Platform), and relevant AI/ML services.
  • Experience with Vector DBs, LangChain, LLMOps platforms, or orchestration tools.
  • Understanding of real-time data processing and API integration within Capital Markets systems.
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.