AI/ML Engineer

Future Works; London; On-site; CAD 171,000 - 214,000; Full time

Job summary

Go Fractional is seeking an AI/ML Engineer to design and build an AI agent system that manages a complex, high-value transaction workflow for a large enterprise client, across multiple stages from engagement to close-out.

You will implement tool integrations, data pipelines, and per-stage agent components, under the Lead AI/Agent Architect, and participate in end-to-end testing across all eight stages with broker-confirmation gates and QA checks.

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.
• Comfort parsing, extracting, and generating documents across formats such as PDF/DOCX and templates.
• Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction from contracts or leases.
• Exposure to commercial real estate or another document-heavy transaction domain is a plus.
• Familiarity with LLM code assistants and agentic engineering to ship faster and with higher quality.
• Hypothesis-driven, milestone-based sprint execution and shipping working components.

Responsibilities

• Per-Stage Agent Build: implement capabilities for individual workflow stages and handoffs.
• Tool & Integration Development: build typed tools for templates, market data, financial analytics, contract extraction, and document assembly.
• Data Pipelines: maintain pipelines against sandbox data and sample data, including property availability.
• Human-in-the-Loop Implementation: encode approval gates so broker confirmation is required for binding steps.
• Quality & End-to-End Testing: validate components and test eight-stage end-to-end workflows.
• Build-Phase Readiness: participate in architecture workshops to ensure solid foundations.

Skills

4+ years in software or ML engineering

Agent Tooling

Python & Data Engineering

Document Processing

Financial & NLP Depth

Domain Exposure

AI-Native Workflow

Agile Execution

Job description

AI/ML Engineer

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.

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.

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.

Employment type: Contract

Work arrangement: New York or US Eastern. We work in our clients' time zones, with regular time in person on client sites.

Compensation: Compensation. A competitive salary.