AI Solution Architect

New York City, NY - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

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

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 GCP) 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.

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

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

Job Description:

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 GCP) 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.