AI/ML Engineer

Future Works

14h • Remote

About The Position

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 running an engagement to design and build an AI agent system that manages a complex, high-value transaction workflow for a large enterprise client, from initial engagement through close-out, across a multi-stage process. As an AI/ML Engineer, you will build agent capabilities in parallel during the build phases, working under the Lead AI/Agent Architect. You will implement the tool integrations, data pipelines, and per-stage agent components that let a full transaction scenario run end to end against sandbox data. Working alongside the Lead Architect, a Lead Business Analyst, and QA, you are accountable for working software: given a new transaction scenario within the client's domain, your components produce the correct artifacts at each assigned stage and request human confirmation only at the documented intervention points.

Requirements

• 4+ years in software or machine learning engineering, with production experience building LLM-powered features or agents.
• Hands-on experience with agent frameworks, tool and function calling, retrieval, and prompt engineering.
• Strong Python and practical experience building data pipelines and integrating structured and unstructured data sources.
• Comfort parsing, extracting, and generating documents across formats such as PDF, DOCX, and structured templates.
• Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction (clause and entity extraction from contracts or leases) is strongly preferred.
• Comfort utilizing LLM code assistants and agentic engineering to ship faster and with higher quality.
• Ability to move quickly in hypothesis-driven, milestone-based sprint cycles, shipping working components and iterating against real evidence.

Nice To Haves

• Exposure to commercial real estate or another document-heavy transaction domain is a plus.

Responsibilities

• Implement agent capabilities for individual workflow stages (for example engagement agreement generation, needs-assessment brief, market survey and long-list scoring, tour management, RFP and proposal analytics, lease abstraction, and close-out and invoicing), building to the orchestration model and stage handoff protocols defined by the Lead Architect.
• Build the typed tools the agents call: template population, market-data query, financial analytics (NER, TI, free rent, NPV), clause and lease-clause extraction, and document assembly.
• Build and maintain pipelines against sandbox and representative sample data, including the property availability data source.
• Encode the approval gates and review checkpoints specified by the architect, so binding steps always route through a broker confirmation.
• Validate components against deal-scenario data and participate in end-to-end testing across all eight stages, checking artifact quality and stage handoff integrity.
• Participate in Phase 1 architecture workshops to ensure the build starts on solid foundations.

Benefits

• Work from anywhere, forever
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed