Platform Architect (New York City, NY)
Enterprise AI Architect setting the AI strategy and architecture for a global investment management firm in NYC: builds reference architectures for agentic AI/RAG, defines governance and security frameworks, and advises executives. Core tech: LLMs, LangChain/AutoGen/CrewAI, vector databases, Snowflake/Databricks, AWS.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 5+ years
- Category
- Architecture
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related discipline
- 10+ years technology architecture experience, including 3-5+ years focused on AI/ML architecture in large enterprise environments
- Deep hands-on expertise with large language models (LLMs)
- Hands-on expertise with RAG architectures
- Hands-on expertise with vector databases
- Hands-on expertise with embedding pipelines
- Hands-on expertise with prompt engineering
- Experience with agent orchestration frameworks such as LangChain, AutoGen, CrewAI, or similar
- Experience designing agentic AI solutions and multi-agent architectures
- Strong background with enterprise data platforms such as Snowflake, Databricks, or similar
- Experience building cloud-native architectures within AWS environments, including AI/ML services
- Ability to create architecture artifacts: reference architectures, technology roadmaps, ADRs, capability assessments
- Experience working within formal enterprise architecture governance processes
- Exceptional communication and stakeholder management skills
- Authorized to work in the United States without current or future sponsorship requirements
Nice to have
- Master's degree or PhD in Computer Science, AI, Machine Learning, Data Science, or related field
- Experience within financial services, asset management, investment banking, fintech, or other highly regulated industries
- Knowledge of AI governance frameworks, model risk management, and evolving AI regulations
- Familiarity with emerging technologies: quantum computing, blockchain, distributed ledger technologies, advanced AI infrastructure
Full description
About the Opportunity
A leading global investment management firm is seeking an Enterprise AI Architect to help define and accelerate the organization's enterprise-wide AI strategy. This is a highly visible role that will partner closely with executive leadership and enterprise architecture teams to establish the architectural foundations for AI adoption across a complex global organization.
The successful candidate will be responsible for developing AI architecture standards, governance frameworks, and enterprise-wide design patterns that enable secure, scalable, and responsible AI deployment across investment, operational, and client-facing functions.
This is a unique opportunity to influence how a major financial institution leverages emerging AI technologies to drive innovation, efficiency, and competitive advantage.
Key Responsibilities
Enterprise AI Strategy & Architecture
- Define and maintain the enterprise AI architecture roadmap, including model infrastructure, data platforms, orchestration layers, integration patterns, and governance controls.
- Develop reference architectures for agentic AI systems, multi-agent workflows, orchestration frameworks, and Model Context Protocol (MCP)-based implementations.
- Design AI solutions supporting front-, middle-, and back-office business functions.
- Drive integration of AI capabilities with enterprise data and content platforms utilizing RAG, vector databases, embeddings, and modern AI tooling.
- Establish standards for AI platform scalability, security, and operational excellence.
Governance, Risk & Compliance
- Design and operationalize AI governance frameworks covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance.
- Define evaluation criteria for foundation models and open-source models, balancing performance, cost, latency, security, and business value.
- Partner with Legal, Risk, Compliance, and Information Security teams to ensure responsible AI deployment.
- Develop security and privacy patterns addressing prompt injection, sensitive data handling, and regulatory requirements.
Enterprise Leadership
- Translate business objectives into AI architecture roadmaps and technology strategies.
- Guide architecture review processes and provide governance for AI-related initiatives.
- Produce executive-level deliverables including technology assessments, architecture blueprints, vendor evaluations, and strategic recommendations.