Senior Algorithm Engineer – Fuel Optimization, Routing & IFTA Logic

We are seeking a Senior Algorithm Engineer to take full ownership of a core system involving fuel optimization, routing, and IFTA-related logic for long-haul trucking operations. This is not a task-based role. This is an ownership role. We are specifically looking for someone who can independently assess an existing system, identify gaps, challenge assumptions, discover edge cases, and drive the algorithm forward without requiring step-by-step direction. Current Situation • A production backend and mobile application already exist. • A fuel optimization engine is currently operating in production. • The system has been tested extensively using real-world trucking scenarios. • Several optimization edge cases have been identified and require architectural analysis and correction. • Documentation exists but should not be assumed to be complete or fully accurate. • The selected candidate will be expected to validate assumptions rather than blindly implement them. Responsibilities • Analyze the existing backend and optimization engine (Node.js / AWS environment). • Determine independently what is working, what is not, and what must change. • Reverse-engineer existing decision logic. • Identify algorithmic flaws, optimization conflicts, and edge cases. • Improve fuel purchasing decisions across entire trips. • Ensure outputs are correct, explainable, and economically optimal. • Propose and drive clear execution plans. • Validate algorithm behavior against real-world scenarios. What This Role Is NOT • Not a role where tasks are handed to you step-by-step. • Not a role for passive execution. • Not a role for waiting on direction. • Not a role focused solely on coding. • Not a role where implementation is considered success if the algorithmic outcome is incorrect. What We Expect • Independent thinking and decision-making. • Ability to challenge assumptions with technical reasoning. • Ownership of outcomes—not just tasks. • Strong systems thinking. • Ability to identify invalid logic before users discover it. • Clear and direct communication. Ideal Candidate • Strong background in algorithms, optimization, operations research, decision systems, or route optimization. • Experience working with complex decision-making engines. • Comfortable working with incomplete or ambiguous systems. • Experience with AWS and backend architectures (Node.js preferred). • Proven ability to reverse-engineer and improve existing systems. • Strong problem-solving and systems-thinking mindset. Nice to Have • Routing and logistics experience. • Fuel optimization experience. • Operations research background. • Cost optimization systems. • Mathematical optimization or decision science experience. Engagement This is a long-term role with the potential to become a key technical leader inside the project. Compensation Model (Important — Please Read Carefully) This role is posted as hourly for visibility, but our internal execution model is milestone-based and tied to verified outcomes. We do not pay for explanations. We do not pay for estimated future results. We pay for verified, working outcomes. Candidate Evaluation Before any engagement begins, candidates will be evaluated using a real-world optimization scenario derived from our production environment. The objective is to determine whether the candidate can think like an owner of the algorithm rather than simply implement instructions. Candidates should be able to: • Analyze the scenario. • Identify the underlying optimization problem. • Explain the correct outcome. • Explain why alternative outcomes are incorrect. • Identify hidden assumptions. • Identify optimization conflicts. • Identify edge cases. • Propose an algorithmic solution. This evaluation is intended to assess reasoning, systems thinking, and optimization capability. No repository access is required for this stage. Evaluation Criteria Candidates will be evaluated on: • Quality of reasoning. • Ability to identify hidden assumptions. • Ability to identify edge cases. • Algorithm design quality. • Quality of implementation approach. • Correctness of final outcome. The evaluation is not based on years of experience, certifications, titles, or tool usage. It is based on demonstrated problem-solving ability. Milestone-Based Execution All work is broken into clearly defined technical milestones. A milestone is only considered complete when ALL of the following are met: • Clear technical objective. • Reproducible validation scenario. • Verified working result. • Demonstrated correctness. Example "Algorithm improved" is NOT sufficient. "Algorithm correctly solves defined optimization scenarios and produces validated outputs" is sufficient. No Partial Credit on Critical Systems For core components (algorithm, optimization engine, routing decisions, critical business logic): • Work is either functional or incomplete. • Partial implementations are not considered complete. • Explanations do not replace results. Ownership Requirement The primary responsibility of this role is not writing code. The primary responsibility is ensuring that algorithmic decisions are correct. Candidates are expected to independently identify: • Invalid assumptions. • Optimization conflicts. • Edge cases. • Reachability issues. • Cost-minimization failures. • Situations where local optimization increases total trip cost. If users discover critical algorithmic flaws before the engineer does, the ownership requirement has not been met. To Apply Please answer the following: 1. How would you approach analyzing an unfamiliar optimization system with incomplete documentation? 2. Describe a situation where a locally optimal decision produced a globally suboptimal result. 3. How would you validate that a routing or optimization algorithm is actually correct and not simply producing plausible-looking outputs? 4. What process would you use to identify hidden edge cases before releasing a production algorithm? We are looking for someone who can own the algorithm, not simply implement it.