Solution Architect

Future Works; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Future Works, a US-focused, AI-native professional services firm, is seeking a Solutions Architect to define the technical blueprint for a rapid 12-week transformation cycle of a North American supply chain relaunch.

You will own end-to-end architecture across data, modeling, and application layers, design a secure, auditable cloud environment, and collaborate with Data Engineers, Full Stack Engineers, and QA to deliver scalable, high‑impact solutions.

Qualifications

• 8+ years in Solutions/Platform Architecture or senior software engineering.
• Experience designing secure, production-grade enterprise systems.
• Hands-on AWS and/or Azure deployment experience with identity, network segmentation, and secret management.
• Knowledge of Python-based services and modern web app architectures.
• Experience with ERP/WMS/CRM or logistics integrations.

Responsibilities

• Own end-to-end architecture across data ingestion, storage, model services, and optimization logic.
• Define and oversee a single-tenant cloud environment with strong security and auditability.
• Collaborate with Data Engineers to shape canonical schema and data transformations.
• Design how predictive models and business rules interact with optimization solvers.
• Set non-functional requirements for performance, resilience, monitoring, deployment, and release readiness.
• Guide engineering teams on trade-offs, sequencing, and implementation standards.

Skills

Cloud design (AWS/Azure)

Python services

APIs and data stores

Enterprise systems integration

Data pipelines and ML components

Security and auditability

Agile delivery

LLM/agentic engineering

Tools

PostgreSQL

REST APIs

Job description

About Future Works

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.

The Role

We are initiating a rapid, 12-week hypothesis-driven transformation cycle designed to stabilize and economically optimize a complex North American supply chain relaunch for a large enterprise client.

As the Solutions Architect, you will define the technical blueprint that makes this transformation possible. You will be accountable for designing the secure cloud environment, shaping the system architecture across data, modelling, and application layers, and ensuring the decision engine is robust enough to move from pilot validation into production use. Working closely with Data Engineers, Business Analysts, Full Stack Engineers, and QA, you will turn a fragmented operational landscape into a secure, auditable, and scalable solution that drives speed, efficiency, and fiscal gain.

Key Responsibilities

• Solution Architecture: Own the end-to-end architecture across data ingestion, storage, model services, optimization logic, and user-facing applications.

• Secure Environment Design: Define and oversee a single-tenant cloud environment that supports rapid delivery while meeting strict requirements for security, access control, auditability, and data isolation.

• Data Platform Collaboration: Work alongside the Data Engineering Lead to shape the canonical schema, integration patterns, and transformation rules required to unify historical freight, order, inventory, and rate card data.

• Decision Engine Design: Architect how predictive models, business rules, and optimization solvers work together to produce clear, defensible recommendations under real operational constraints.

• Production Hardening: Establish the non-functional requirements for performance, resilience, monitoring, deployment, rollback, and release readiness so the platform can operate reliably beyond the pilot phase.

• Cross-Functional Technical Leadership: Translate business requirements and operational logic into clear technical decisions, guiding engineering teams on trade-offs, sequencing, and implementation standards.

Required Skills and Experience

• 8+ years of experience in Solutions Architecture, Platform Architecture, or senior software engineering, with a strong track record of designing secure, production-grade enterprise systems.

• Cloud Expertise: Hands‑on experience designing and deploying systems in AWS and/or Azure, including identity, network segregation, secrets management, and secure environment configuration.

• Technical Breadth: Strong working knowledge of Python‑based services, APIs, PostgreSQL or similar data stores, and modern web application architectures.

• Systems Thinking: Proven ability to design end‑to‑end solutions that connect data pipelines, business logic, analytics or machine learning components, and operational user interfaces.

• Integration Experience: Practical experience working around enterprise systems such as ERP, WMS, CRM, or logistics platforms, especially in environments where data is fragmented and source systems cannot be changed easily.

• Domain Knowledge: Previous experience working with supply chain, logistics, fulfilment, or ERP‑heavy operational environments is highly preferred. You should understand the realities of freight flows, inventory positioning, allocation logic, warehouse constraints, and the downstream cost of operational exceptions.

• Regulated Delivery: Good judgment around auditability, deterministic workflows, traceability, and release control in environments where technical decisions must be explainable and reviewable.

• Agile Execution: Ability to work effectively in fast, hypothesis‑driven delivery cycles where the focus is on proving value quickly without creating unnecessary technical debt.

• AI‑Native Workflow: Comfort utilizing LLM code assistants and agentic engineering to improve speed, quality, and architectural clarity.