AI/ML Engineer

Future Works; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote work

Equity opportunity

Profit-sharing bonuses

Job summary

Future Works is a US-focused, AI-native professional services firm building operational AI and data systems. We are a team of “Time Benders” on a mission to collapse timelines to operational transformation for large enterprise clients.

As an AI/ML Engineer, you will build agent capabilities across multiple stages and integrate tools, data, and components to run end-to-end transaction scenarios. You will work with a Lead AI/Agent Architect, a Lead Business Analyst, and QA to ensure reliable

Qualifications

• 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.
• Document processing across formats such as PDF, DOCX, and structured templates.
• Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction.
• Exposure to commercial real estate or other document-heavy transaction domains is a plus.
• AI-native workflow using LLM code assistants and agentic engineering to ship faster and with higher quality.
• Agile execution in hypothesis-driven, milestone-based sprint cycles.

Responsibilities

• Per-Stage Agent Build: implement agent capabilities for individual workflow stages according to the Lead Architect.
• Tool & Integration Development: build typed tools the agents call, like template population and market-data queries.
• Data Pipelines: maintain pipelines against sandbox data, including property availability data.
• Human-in-the-Loop Implementation: encode approval gates so broker confirmation is required at checkpoints.
• Quality & End-to-End Testing: validate components and test across all eight stages.
• Build-Phase Readiness: participate in Phase 1 architecture workshops to ensure solid foundations.

Skills

LLM-powered features

Agent tooling

Python & data

Document processing

Financial analytics

NLP depth

Domain exposure

AI-native workflow

Agile execution

Tools

Agent frameworks

Tool calling

Retrieval

Prompt engineering

Data pipelines

Document assembly

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 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.

Key Responsibilities

• Per-Stage Agent Build: 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.

• Tool & Integration Development: 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.

• Data Pipelines: Build and maintain pipelines against sandbox and representative sample data, including the property availability data source.

• Human-in-the-Loop Implementation: Encode the approval gates and review checkpoints specified by the architect, so binding steps always route through a broker confirmation.

• Quality & End-to-End Testing: Validate components against deal-scenario data and participate in end-to-end testing across all eight stages, checking artifact quality and stage handoff integrity.

• Build-Phase Readiness: Participate in Phase 1 architecture workshops to ensure the build starts on solid foundations.

What We’re Looking For

Required Skills and Experience

• 4+ years in software or machine learning engineering, with production experience building LLM-powered features or agents.

• Agent Tooling: Hands-on experience with agent frameworks, tool and function calling, retrieval, and prompt engineering.

• Python & Data Engineering: Strong Python and practical experience building data pipelines and integrating structured and unstructured data sources.

• Document Processing: Comfort parsing, extracting, and generating documents across formats such as PDF, DOCX, and structured templates.

• Financial & NLP Depth: Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction (clause and entity extraction from contracts or leases) is strongly preferred.

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

• AI-Native Workflow: Comfort utilizing LLM code assistants and agentic engineering to ship faster and with higher quality.

• Agile Execution: Ability to move quickly in hypothesis-driven, milestone-based sprint cycles, shipping working components and iterating against real evidence.

Our Culture & Benefits

We believe that breakthrough results are driven by breakthrough experiences. Our culture is built on a foundation of freedom, high performance, and our seven core values.

Our Core Values

• AI native - We use AI as a natural extension of our abilities to deliver faster, smarter, and better work.

• Delivering joy - We underpromise and overdeliver, creating delight for our clients and our team.

• Smooth & fast - We believe speed is the result of precision, flawless systems, and calm execution, not frantic effort.

• Selfless - We proactively make work easier for others and measure our success by the success of the team.

• Candid - We are direct, honest, and clear with each other, believing that transparent feedback is a gift.

• Pursuing excellence - We are obsessed with quality and empower each other to break through boundaries and set new standards.

• Ever evolving - We are relentlessly curious and improve every single week, sharing our learnings openly to elevate the entire organization.

Benefits & Perks

• Work from anywhere, forever - We are a fully remote and global team. We trust you to manage your time and energy to deliver exceptional results.

• 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.