Investment Systems Director

Pretium is a specialized investment firm focused on U.S. residential real estate, residential credit, and corporate credit. Pretium was founded in 2012 to capitalize on investment and lending opportunities arising as a result of structural changes, disruptions, and inefficiencies within the economy. Pretium has built an integrated analytical and operational ecosystem within the U.S. housing, residential credit, and corporate credit markets, and believes that its insight and experience within these markets create a strategic advantage over other investment managers. Pretium’s platform has more than $57 billion of assets, comprising real estate investments across nearly 90 markets in the U.S., and employs approximately 7,000 people across 50 offices, including its New York headquarters, Miami, London, Seoul, and Sydney. 

With expert business service capabilities, Pretium Enterprise Services (“PES”), is integral to the growth, innovation, and transformation of Pretium’s global operating companies. Partnering with internal and external businesses and stakeholders to rapidly unlock value for its customers, PES delivers with excellence and ownership, enabling scalable growth.

Own the firm's data and AI platform architecture while serving as the primary technology and data partner to the Investment Management function — embedded deeply enough to drive the financial close process, weekly P&L, and fund economics infrastructure. This person decides what data looks like before it reaches any product, model, or analyst, and what investment systems look like before they reach any fund manager or portfolio analyst.

50%

Data & AI Platform Architecture

Owns the warehouse architecture, transformation layer, feature and retrieval infrastructure, and the governance model that keeps the system coherent across all OpCos.

50%

Forward Deployed Engineering

Embedded with IM — financial close automation, weekly P&L, fund economics, returns infrastructure, and AI-assisted analytics for investment teams.

01

AI Platform

Feature store, vector database, embedding strategy, retrieval architecture, model registry, and evaluation pipelines — so AI product delivery is repeatable, not bespoke each time.

02

Data Platform

Snowflake hub-and-spoke design, dbt transformation layer, and materialization strategy across all domains and OpCos — the trusted foundation every team builds against.

03

Data Governance

Data contracts, ownership models, schema standards, and quality SLAs. Owns data governance. Owns the data dictionary and business glossary as the firm's semantic source of truth.

04

Financial Close & Fund Systems

Own the infrastructure behind weekly P&L, fund economics, and returns. Automate the financial close process and eliminate manual dependencies across fund finance and IM workflows.

05

IM Business Partnership

Primary technology counterpart to fund managers and investment teams. Translates investment problems into platform solutions — present in investment conversations, not waiting to be consulted.

06

Platform Enablement

Maintains the firm's reference architecture and approves new platform components and data tooling. Partners with OpCo teams to translate domain use cases into platform requirements.

AI PLATFORM

• Build and maintain the feature store — versioned, reusable features available to all model teams without per-use-case extraction
• Own retrieval infrastructure: vector database, embedding model selection, chunking/indexing strategy, and hybrid search architecture
• Define model registry standards — versioning, lineage, evaluation baselines, and promotion gates from dev to production
• Build observability pipelines for deployed AI — drift detection, output quality logging, and ground-truth feedback loops

DATA PLATFORM

• Own Snowflake architecture — schema topology, role-based access, and hub sharing model across OpCos
• Define dbt layer conventions: naming, materialization, clustering, and incremental patterns across all model builds
• Own firm-level golden records (Master Loan Ledger and domain equivalents) as governed data products with defined producers and consumers
• Set ingestion standards — schema registration and lineage documentation required before any source is consumed downstream

DATA GOVERNANCE & FUND INFRASTRUCTURE

• Run the Data Governance Council — domain ownership, dispute resolution, and escalation to senior leadership
• Approve all data contracts for cross-OpCo pipelines — producer SLA, schema, and consumer expectations defined before go-live
• Maintain the data dictionary and business glossary as authoritative semantic definitions across the firm
• Own data classification (PII, sensitive, internal) and enforce access control policy across the lake

FINANCIAL CLOSE & FUND INFRASTRUCTURE

• Own the end-to-end financial close process — identify manual steps, automate systematically, and reduce cycle time across fund finance
• Build and maintain weekly P&L, fund economics, and returns infrastructure — reliable, auditable, and available without analyst intervention
• Partner with fund controllers and portfolio analytics on data model design for NAV, performance attribution, and fund-level reporting
• Identify and implement AI-assisted automation across IM workflows — prioritized by investment team impact

IM BUSINESS PARTNERSHIP

• Serve as the embedded technology partner to IM leadership — present in investment conversations, not waiting to be consulted after decisions are made
• Translate investment team pain points into platform requirements, data products, and engineering priorities
• Own the relationship with Palantir FDEs on the Resi Credit track — coordinating sprint priorities and ensuring delivery aligns with IM objectives
• Build and develop a small, focused engineering team embedded within the IM function

PLATFORM ENABLEMENT

• Maintain the firm's reference architecture — how data flows from OpCo source systems through to AI/ML serving
• Review and approve new platform components and data tooling before adoption
• Partner with OpCo data and product teams to translate domain use cases into platform requirements

AREA

WHAT WE'RE LOOKING FOR

AI/ML Infrastructure

Hands-on with feature stores, vector databases (Pinecone, pgvector, Weaviate), and LLM orchestration (LangChain, LlamaIndex). MLflow or equivalent for model lifecycle.

Cloud Data Warehouse

Deep Snowflake fluency — architecture, clustering, RBAC, sharing, and multi-tenant hub-and-spoke design across business units.

Data Transformation

dbt expertise: materialization, incremental models, testing, source vs. ref discipline. Ability to set and enforce layer conventions across engineering teams.

Data Governance

Designed and operationalized data contracts, ownership models, and quality SLAs. Run governance councils across teams with competing priorities.

Financial Systems Fluency

Has built or owned weekly P&L, fund economics, and financial close infrastructure. Speaks the language of fund controllers and portfolio managers without a translator.

Forward Deployed Instinct

Operates as a business partner, not a ticket-taker. Surfaces problems before they're articulated and prioritizes by investment team impact.

Quantitative Fluency

Reasons about feature engineering tradeoffs, statistical validity, and model evaluation design — as platform owner gating what data reaches models and how it's structured.

Earned Authority

Enforces platform standards across teams without direct control. Builds credibility through judgment, not org chart position. Comfortable leading a small team in a high-ambiguity environment.

AI Layer Operational

Feature store + vector retrieval serving ≥2 production AI products

Weekly P&L Live

Automated P&L and returns infrastructure running without analyst intervention

Financial Close Cycle

Measurable reduction in manual steps and time-to-close across fund finance

Data Contracts Live

All critical cross-OpCo pipelines covered with defined producer SLAs

Golden Records

Master Loan Ledger + ≥2 domain records live as governed assets

Schema Compliance

>90% of new dbt models pass governance review on first submission

This position offers the opportunity to join a collegial, entrepreneurial firm committed to the personal and professional growth of its team members and to maintaining a positive, encouraging work environment where people enjoy working together. The company offers a comprehensive benefits and perks package, including:

• 401(k) plan with an employer match
• Health, dental, vision and life insurance
• Paid Time Off (PTO)
• 11 firm holidays
• Hybrid office/work from home arrangement (in office minimum of four days per week)
• Annual base salary range for this role is expected to be between $175,000 - $225,000
  • The actual salary will depend on various factors, including but not limited to a candidate’s experience and credentials, salary expectations of applicable candidates, and other applicable market conditions.
• Annual year-end bonus eligible

Pretium Enterprise Services is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity or expression, genetic information, marital status, sexual orientation, national origin, disability, age, veteran status, or any other characteristic protected by federal, state, or local law.