Lead Applied AI Engineer

Salary: $92,000 - 132,000 per year

Requirements:

8+ years of experience building production software or machine-learning systems, including at least 2 years building LLM applications shipped to real users. Demonstrated ability to set technical direction for AI or ML systems, including selecting architectures, tools, and standards adopted by others. Experience mentoring, coaching, or leading engineers, formally or as a technical lead. Hands-on production experience with retrieval-augmented generation and agentic or tool-using systems, including prompt and configuration versioning, regression testing, rollback procedures, and understanding of common failure modes. Good judgment in selecting models and vendors, engineering prompts and context, and deciding when fine-tuning is appropriate. Experience making generative AI systems reliable in production through guardrails, evaluation, observability and tracing, and cost and latency management. Strong Python software engineering skills, including production services, APIs, and testing, plus experience deploying on a major cloud platform. Track record of turning ambiguous problems into shipped products with domain experts, product, and engineering; influencing executives and stakeholders; and communicating candidly when an approach is unlikely to work. A degree in computer science or a related field, or equivalent practical experience. An advanced degree is welcome but not required. Energy, oil and gas, or industrial experience is a plus, but not required. Document AI experience, including OCR or layout-aware or multimodal extraction from contracts, forms, or scanned documents, is a plus. Fine-tuning or deploying open-weight models is a plus. Experience with Azure or AWS AI services, such as Azure OpenAI or Amazon Bedrock, is a plus. Experience hiring AI or ML engineers or establishing an applied AI function is a plus. Experience on cross-functional or innovation teams that take prototypes to customers is a plus. Responsibilities:

Work with industry experts to identify customer workflow problems suited to generative AI or agents, and determine when another approach is more suitable. Design and build LLM applications, including retrieval-augmented generation, agents, and tool use, using PakEnergy products and data. Assess and select foundation models and providers, develop prompts and context, and fine-tune models when evidence supports doing so. Build AI systems that extract and interpret leases, contracts, tickets, and other energy documents, incorporating human review where needed. Establish safety guardrails, protect customer data, manage cost and latency, and implement monitoring and fallbacks. Assess and mitigate security risks related to agent actions, tools, permissions, and customer-data access. Work with Engineering to deliver generative AI features in production, with observability, tracing, and operational monitoring. Partner with the Lead Data Scientist on data, evaluation, and classical machine learning, incorporating evaluation methods and models into applied AI systems where they improve outcomes. Collaborate with solution engineers on customer pilots, configure and tune features for customer data, and apply pilot findings to product development. Set the Labs applied AI technical direction, including architecture, reusable patterns and components, and responsible AI standards. Document the Labs applied AI practices, mentor and coach colleagues, and help shape future team roles and hiring plans. Technologies:

AI AWS Azure Cloud Fine-tuning LLM Machine Learning Python Security Architect Embedded Mobile More: We are PakEnergy, whose software supports land, production, accounting, and transportation operations for more than 2,300 oil and gas companies. Our Innovation Lab brings together product industry experts, a Lead Data Scientist, solution engineers, and this hands-on Lead Applied AI Engineer role, which reports to our Chief Product Officer and will own generative AI and agentic systems. The Lab identifies valuable customer problems, prototypes solutions using operational energy data, and brings proven ideas into production. Our existing AI work includes lease-provision analysis, document processing for transportation, and well optimization. This is a founding applied AI role with autonomy over technical direction and a potential path to building and leading a team as the Lab grows. We offer a casual business environment, generous paid time off, employer-sponsored health benefits, and a retirement savings plan, including a 401(k) in the US. The preferred locations are our offices in Frisco, Texas, or Calgary, Alberta; exceptional candidates may be considered for remote work with required onsite attendance. We are an equal opportunity employer committed to an inclusive hiring process and welcome applicants of all backgrounds. last updated 43 week of 2026