Position: AI Solution Architect
Location: Hybrid/Midtown New York City or 100% Remote
Duration: 12 Months
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.
