Lead Applied AI Engineer

Role and mission

Team and product context

What you will do

• Find customer workflow problems suited to GenAI or agents with industry experts, and identify when GenAI is not appropriate.
• Architect and build LLM applications using RAG, agents, and tool use with PakEnergy products and data.
• Select foundation models and providers, engineer prompts and context, and fine-tune when evidence supports it.
• Build document AI for leases, contracts, tickets, and other energy documents, with human review where accuracy requires it.
• Own guardrails and safety, protect customer data, manage cost and latency, and provide monitoring and fallbacks.
• Assess security risks associated with agent actions, tools, permissions, and customer-data access.
• Ship production GenAI features with Engineering and instrument agent observability, tracing, and operational monitoring.
• Partner with the Lead Data Scientist on evaluation and classical ML, and integrate their evaluations or models where they improve outcomes.
• Run customer pilots with solution engineers, tune features on real customer data, and apply pilot findings.
• Set Lab architecture, reusable patterns, components, standards, and responsible AI practices; document methods and mentor teammates.

What you bring

• 8+ years building production software or ML systems, including 2+ years building LLM applications shipped to users.
• Experience setting technical direction for AI or ML architectures, tooling, and standards adopted by others.
• Experience mentoring, coaching, or leading engineers as a formal or technical lead.
• Production RAG and agent/tool-system experience, including versioning, regression tests, rollback procedures, and knowledge of failure modes.
• Sound model and vendor selection, prompt and context engineering, and fine-tuning judgment.
• Production reliability experience covering guardrails, evaluation, observability, tracing, cost, and latency.
• Strong Python engineering across production services, APIs, and tests, plus deployment on a major cloud platform.
• Experience turning ambiguous problems into shipped products with domain, product, and engineering partners and influencing stakeholders.
• Computer science or related degree, or equivalent practical experience; an advanced degree is not required.

Helpful additional experience

• Energy, oil and gas, or industrial experience is a plus, not a requirement.
• Document AI, OCR, layout-aware or multimodal extraction is advantageous.
• Fine-tuning or deploying open-weight models is advantageous.
• Azure or AWS AI services, including examples such as Azure OpenAI or Amazon Bedrock, are advantageous.
• Hiring AI or ML engineers, building an early applied AI function, or taking prototypes to customers on cross-functional teams is advantageous.

Location and work arrangement

• In-office locations in Frisco, Texas or Calgary, Alberta are preferred.
• Exceptional candidates may be considered for a remote arrangement with a required on-site cadence.

Benefits

• Benefits include a casual business environment, generous paid time off, employer-sponsored health benefits, and a retirement savings plan, including a 401(k) in the US.

About PakEnergy