Job DescriptionForward Deployed AI Engineer Location: hybrid/in-officeFull Time Contract:6-24MonthsAbout the RoleThis is a hybrid/in-office role for someone based in Calgary, Alberta. You'll work closely with client operations, engineering and IT teams to turn real operational problems into working AI products: LLM applications, agents, RAG pipelines and ML models. You'll scope the problem, write the code, integrate with client data and systems, and see it through to daily use. Experience in the oil and gas industry is preferred. This role will be forward-deployed into a client organization in the Energy sector. They may join an existing team or work independently.
Key Responsibilities- Partner with the client. Work with engineers, operators and control room staff to find high-value problems. Examples: production optimisation, predictive maintenance, drilling performance and document-heavy workflows.
- Scope and prototype fast. Turn a vague task into a defined use case with success metrics. Ship a working prototype on real data within weeks, not months.
- Build production systems. Develop LLM applications, agents, RAG pipelines and ML models. Take them from notebook to deployed, monitored service.
- Integrate with operational data. Connect to historians, SCADA/DCS data, ERP and maintenance systems, and the document stores where engineering knowledge lives.
- Deploy in constrained environments. Work within OT/IT segregation, on-prem or private cloud, limited connectivity at remote sites, and strict security reviews.
- Drive adoption. Train users, gather feedback and iterate until the tool is part of daily operations.
- Feed the product. Turn repeated client patterns into reusable components and accelerators for the wider Type B team.
- Own the relationship technically. Be the trusted technical voice for client stakeholders, from field supervisors to the CTO.
Qualifications- Bachelor's degree in Computer Science, IT, or related field preferred; diploma or equivalent
- 4+ years building and shipping software with full-stack capabilities, including at least 2 years on ML or LLM-based systems in production.
- Strong Python. You should be comfortable with SQL and with building APIs and services (FastAPI or similar).
- Hands-on experience with LLM applications: RAG, agents and tool use, prompt and eval design, and working with frontier model APIs.
- Solid data engineering: pipelines, messy time-series and unstructured data, and data quality in the real world.
- Deployment experience on at least one major cloud (Azure, AWS or GCP), plus Docker, CI/CD and basic MLOps or LLMOps.
- A record of client-facing or cross-functional work. You can explain a technical trade-off to a plant manager and to a data architect.
- An owner's mindset. You are comfortable with ambiguity, you ship with incomplete information, and you follow through to adoption.
- Based in the Calgary, Alberta.
Nice to Have- Experience in the oil and gas industry (preferred).
How to Apply:Ready to elevate your career as an AI Engineer? Join our innovative team and showcase your expertise , simply submit your resume through the link, and we'll take it from there.
