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About the Role

We build custom data and AI platforms for institutional real estate owners, operators and fund managers. These are fixed-fee, gate-based cycles that start with a trusted data foundation and end with the views, agents and reports that each group inside the client's business uses in their work. As the Solution Architect, you define the technical blueprint that makes that possible. You are accountable for the architecture of a client-owned platform inside their own cloud environment, for the read-only integration pattern across every system their portfolio runs on, for the AI layer that maps, checks, abstracts and answers on top of it, and for the security, auditability and handover standards that let the client's own team extend the platform after we leave. Working with the data and technology lead, full-stack engineers and a partner on business outcomes, you turn a fragmented landscape into one asset record that ties.

Responsibilities

Own the end-to-end architecture across ingestion, storage, the canonical data model, data quality, model and agent services, reporting and user-facing applications.
Define a single-tenant platform inside the client's own cloud tenancy that meets their requirements for identity, access control by fund and role, network isolation, secrets management, audit logging, test environments and backup.
Work with the data and technology lead to shape the schema that links funds, entities, assets, tenants, leases, loans and JV positions, plus the mapping rules that bring each third-party operator's chart of accounts into the client's format.
Design the connector pattern for systems that cannot be changed and must never be written back to.
Architect how a reported figure is produced and defended: deterministic calculations, reconciliation against source, data checks and tolerance thresholds, exception routing to the responsible deal team, lineage back to the source document, and immutable snapshots for closing models, quarterly projections and month-end.
Architect where agents do the work and where they stop: mapping new operator data, abstracting loan and JV terms, retrieval that answers portfolio questions with sources cited, drafted commentary, client approval of mappings, rules and KPI definitions, evaluation and guardrails, and a model-agnostic design so the client chooses the models.
Set the non-functional requirements for performance, resilience, monitoring, deployment, rollback and release readiness, so the platform holds up beyond the pilot and through a quarter-end close.
Design the migration of history off the incumbent platform, the parallel run, and the evidence the client needs to sign off that the old system can be switched off.
Translate business and operational logic into clear technical decisions, guiding the team on trade-offs, sequencing and standards against a fixed fee and client-signed gates.
Shape the target operating process alongside the architecture, and build the value baseline with the client's finance team so the investment is measured against their own numbers.
Document the architecture, the decisions behind it and the operating runbook, so the client's named platform owner and team can extend the platform once the engagement ends.

Requirements

5+ years in Solution Architecture, Platform Architecture or senior software engineering, with a strong track record of designing secure, production-grade enterprise systems.
Hands-on design and deployment in Azure, which is the common client environment, and ideally AWS as well, covering identity, network segregation, secrets management and secure environment configuration.
Familiarity with Fabric or Synapse and with Power BI is a strong plus.
You have designed a lakehouse or warehouse with layered zones (raw, mapped, validated and locked, or the medallion equivalent), ELT orchestration, reconciliation and data quality frameworks, and immutable snapshots.
Strong working knowledge of Python-based services, APIs, PostgreSQL or similar data stores, and modern web application architectures.
Proven ability to design end-to-end solutions that connect data pipelines, business logic, analytics or machine learning components, and operational user interfaces.
Practical experience around enterprise systems you cannot change: property accounting (Yardi, MRI, RealPage), investor and fund platforms (Juniper Square), deal and leasing platforms (Altrio, VTS), valuation tools (ARGUS), and SharePoint and Excel as de facto systems of record.
Equivalent experience in another fragmented, ERP-heavy landscape counts if the real estate learning curve will be short for you.
Institutional real estate strongly preferred: fund, entity, asset and JV hierarchies, rent rolls and operating statements, budget vs actual and T-12, debt covenants and test dates, locked underwriting as a benchmark, and the downstream cost of a number that does not tie.
Good judgment around traceability, deterministic workflows, explainability and release control, in a setting where a figure shown to an investment committee has to be defensible back to its source.
LLM-based extraction, retrieval with cited sources, agent orchestration, evaluation and guardrails, and clear judgment about where AI should not touch a reported number.
Ability to work effectively in fast, hypothesis-driven delivery cycles where the focus is on proving value quickly without creating technical debt someone else inherits.
Comfort utilizing LLM code assistants and agentic engineering to improve speed, quality, and architectural clarity.
Able to run technical workshops with client data owners and defend architecture decisions in front of a CFO, COO or head of technology.
Overlap with US Eastern business hours for workshops, gate reviews and client sessions.

Skills

Solution Architecture
Platform Architecture
Software Engineering
Azure
AWS
Fabric
Synapse
Power BI
Lakehouse architecture
Warehouse architecture
ELT orchestration
Data quality frameworks
Python
APIs
PostgreSQL
Web application architectures
Systems thinking
Enterprise systems integration
Yardi
MRI
RealPage
Juniper Square
Altrio
VTS
ARGUS
SharePoint
Excel
Institutional real estate
AI architecture
LLM
Agile execution
AI-native workflow
Client-facing presence

Location

US-focused

Work Type

Full-time

Experience Level

5+ years

Benefits

Connect deeply. We gather for immersive, all-expenses-paid company retreats in unique locations to connect, learn, and grow together.
Share in the upside. A competitive compensation package including equity, bonuses, substantial participation in company profits with a clear growth path to C-Level leadership based on performance.

About the Company

Future Works is a US-focused, AI-native professional services firm building operational AI and data systems.
Our foundation beliefs are simple: optimization lowers need for resources, which increases sustainability and resilience.
We are a team of "Time Benders" on a mission to collapse timelines to operational transformation of high footprint companies in energy, real estate, data and beyond.
Together, we master velocity.
We achieve our mission by building flawless, AI-powered systems.
Our technology is already far more advanced than that of boutique services firms, but we are only getting started and the road from here leads to becoming world's best Service-as-Software company.
Regardless of the specific role, our ideal candidate will always have a keen interest in building symbiotic human-AI systems both individually and for teams; high energy, high agency and a certain passion for bending time.