Time since we first saw it
Day 124
Up longer than most. Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
AI/ML Engineer
Reads like an AI Engineer role: building products on existing AI models.
Canada · United States · Canada
Open 4 months, first seen by us 124 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Contract — employment source
Employment type: Contract
From the employer’s posting- Team
Technology — team source
Department: Technology
From the employer’s posting
What you’ll work on
Full postingImplement agent capabilities for individual workflow stages, such as lease abstraction and tour management
Build typed tools for template population, market-data queries, financial analytics, and clause extraction
Build and maintain data pipelines against sandbox and sample data, including property availability data
Encode approval gates so binding steps route through broker confirmation
Validate components against deal-scenario data and take part in end-to-end testing across eight stages
From the employer’s posting
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)
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.
About Future Works
Large companies spend billions on consulting and implementation projects to adopt new technology.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an errorOpen 4 monthsWe first saw this posting 124 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 12, 2026124 days ago
- Recorded sightings
- 42
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Future Works is hiring
1 open job
- No new data jobs since July
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
Where the posting names them
- 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.
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Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
About Future Works The Role Key Responsibilities What We're Looking For Our Culture & Benefits
Large companies spend billions on consulting and implementation projects to adopt new technology. Most of that work is slow and expensive, and too often it fails to deliver. Future Works replaces it. We rebuild the operations that move a company's P&L in twelve-week cycles, run by senior experts and fleets of AI agents, with our fees tied to outcomes our clients' own finance teams verify. We deliver in twelve weeks what incumbents quote at two years.
We work with large companies in energy, construction, real estate and other asset-heavy industries. Every role here is built around humans and agents working as one system. Whatever the seat, we look for high energy, high agency and a real interest in building with AI.
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.
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.
We believe that breakthrough results are driven by breakthrough experiences. Our culture is built on freedom, high performance and our core values. You can read more about our values and how we work on our careers page: https://future.works/careers
Benefits & Perks
New York or US Eastern. We work in our clients' time zones, with regular time in person on client sites.
Compensation. A competitive salary.
Source details
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- Location & working pattern
Canada
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