6 months ago
Responsibilities
- Design scalable ingestion pipelines across custodians such as Schwab, Fidelity, and Pershing and internal financial systems.
- Build and evolve canonical models for accounts, positions, transactions, balances, corporate actions, and household hierarchies.
- Define the financial data ontology and enforce strong data contracts across services.
- Implement reconciliation frameworks and golden-source resolution across multi-vendor datasets.
- Engineer AI-ready data layers optimized for embeddings, vector search, and retrieval-augmented generation architectures.
- Structure financial datasets to improve prompt reliability and LLM output consistency.
- Architect closed-loop agent-driven systems that monitor, reason over, and autonomously remediate data inconsistencies.
- Implement observability, lineage, governance, and fine-grained access controls across regulated datasets.
Requirements
- At least 5 years of experience building production-grade data platforms.
- Deep SQL expertise and strong Python skills for data engineering.
- Experience designing canonical schemas and resolving inconsistencies across vendor datasets.
- Strong understanding of custodial financial data, including positions, trades, balances, performance, and corporate actions.
- Familiarity with embeddings, vector databases, and retrieval architectures.
- Exposure to prompt engineering and structured context design for LLM systems.
- Knowledge of MLOps fundamentals including versioning, monitoring, and reproducibility.
- Comfort with AWS data services including S3, Lambda, ECS, Glue, Redshift, and OpenSearch, as well as event-driven orchestration.
- Wealth management or capital markets experience is a bonus.
- Experience integrating OpenAI or Anthropic APIs into production systems is a bonus.
- Experience designing retrieval schemas for AI agents is a bonus.
- Experience with authorization and policy platforms such as OSO or Auth0 is a bonus.
- Experience implementing fine-grained access control for AI-driven systems is a bonus.
- Familiarity with GitHub-based CI/CD workflows and automation is a bonus.
- Experience with data governance, lineage, and compliance controls is a bonus.
Benefits
- Book clubs, seminars, and peer learning sessions
- Full health benefits
- 401(k) matching and Roth IRA options
- Unlimited PTO
- Collaborative work across product, design, and engineering
Categories
AI ApplicationsData Engineering
About Farther
Farther is a technology-driven registered investment advisor that provides wealth management, financial planning, and cash management through a platform used by independent advisors and their clients. The company builds tools, including an AI assistant, to help advisors manage portfolios and client workflows. Founded in 2019 and headquartered in New York, it is privately held and manages over $5 billion in assets for 5,000 clients.