AI/ML Architect

AI/ML Architect

Location: Washington, DC
Duration: 3 months will extend depending on the project

Financial experience is a must have

Position Summary:
As the AI Architect, you will play a foundational role in designing the next-generation platform that blends AI, machine learning, LLMs, and financial domain intelligence to augment client s research workflows across private equity, real assets, credit, and infrastructure.
You ll lead the technical vision and design of a system that ingests structured and unstructured financial and market data, applies intelligent analytics, and enables personalized, explainable insights for deal teams, portfolio managers, and senior leadership.

Key Responsibilities:
Platform & Solution Architecture Lead end-to-end architecture for client's AI Investment Research Platform, aligning with enterprise architecture and security standards.
Architect scalable data pipelines and AI services to handle ingestion, transformation, and enrichment of internal and external financial data sources (e.g., SEC filings, earnings transcripts, market news, proprietary deal data).
Design modular components to support use cases like thematic search, smart summarization, investment memo generation, and risk analysis.
Implement and optimize advanced NLP and LLM-based models for tasks such as document classification, entity recognition, semantic search, and RAG (retrieval-augmented generation).
Partner with Data Science, TechOps, and Investment teams to ensure models are explainable, secure, and aligned with financial domain needs.
Establish frameworks for continuous learning, versioning, monitoring, and governance using ML Ops best practices.
Architect robust, cloud-native AI infrastructure using AWS (preferred), leveraging services like SageMaker, Bedrock, Lambda, Glue, and Redshift.
Guide containerization and orchestration using Docker, Kubernetes, and Terraform to enable scalable deployments across environments.
Serve as a strategic technical partner to senior investment professionals, product managers, and data teams.
Lead architecture review sessions, drive buy-in for strategic decisions, and ensure alignment with client s digital transformation goals.
Evaluate emerging technologies and AI vendors to assess applicability in client s ecosystem (e.g., vector databases, multimodal AI, FinLLMs).
Qualifications:
10+ years of experience in AI/ML architecture or engineering, including at least 3 years leading design for enterprise-scale platforms.
Proven experience applying AI to financial services, asset management, or capital markets.
Deep understanding of investment research workflows is a strong plus.
Technical expertise in: NLP and LLMs (e.g., GPT, Claude, Cohere, Llama, BloombergGPT)
ML frameworks: PyTorch, TensorFlow, Scikit-learn
Data platforms: Snowflake, SQL, Databricks, Apache Spark Vector stores and RAG architectures (e.g., FAISS, Pinecone, Weaviate)
Hands-on experience with cloud-native ML architectures, preferably on AWS.
Strong knowledge of enterprise architecture, data governance, and cybersecurity in a regulated financial environment.
Excellent communication skills, including the ability to present to C-suite and investment committee stakeholders.
Experience at a private equity, hedge fund, or institutional asset manager.
Familiarity with ESG data, alternative data sources, or portfolio company insights.
Experience designing AI copilots or analyst assistants using retrieval-based methods and fine-tuned LLMs.