Build and evolve Alwin’s agentic runtime for audit, writing production code, improving agent accuracy and reliability, and scaling performance while guiding technical direction across teams.
Principal Software Engineer
📜 Description
- Define multi-year technical strategy and architecture with product and engineering leadership.
- Set standards for scalable, reliable, maintainable systems with security, compliance, fraud prevention, and regulatory needs built in.
- Turn ambiguous challenges into proposals with clear scope, trade-offs, and build, buy, or partner decisions.
- Reduce technical debt and recurring failures while improving delivery using throughput, cycle time, CFR, and MTTR metrics.
- Lead the AI-native transformation, including AI-ready systems, SDLC and context engineering standards, and production AI capabilities.
- Set technical direction for the AI Enabling Team, coach senior engineers, shape senior hiring and promotion, and communicate strategy to executives.
🛠️ Requirements
- 15+ years building software, with 4+ years at Staff, Principal, or equivalent technical-leadership scope across multiple teams.
- Track record defining and delivering multi-year architecture for high-scale, distributed, transactional systems.
- Deep expertise in distributed systems, financial domain modeling (money movement, ledgering, identity), observability, CI/CD, and cloud infrastructure.
- Evidence of measurable impact on reliability (CFR, MTTR, incident reduction), cost of ownership, or delivery speed.
- Several years designing and shipping ML/AI systems in production at scale, including agentic or LLM-based systems.
- Familiarity with MLOps/LLMOps tooling and production observability for AI.
- A point of view, backed by results, on transforming a legacy engineering organization into an AI-native one.
- Preferred experience in fintech, payments, lending, or another regulated industry, with hands-on work on security, fraud, and compliance; ideally shipping AI in credit, risk, collections, fraud, or underwriting.
- Experience partnering directly with C-level leaders and translating strategy into technical roadmaps.
- Proven record of growing senior engineers into Staff-level leaders.
Full job description
About Kueski
At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for nearly 30% of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.
We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive workplace. Our commitment to excellence and ethical business practices has earned us multiple industry recognitions. In 2024, we were named one of the World’s Top FinTech Companies by CNBC and recognized as one of the most ethical companies in Mexico by AMITAI. Additionally, we were certified as a Best Place to Work for LGBTQ+ Equality by HRC Equidad MX 2025 and ranked among the Best Companies for Female Talent by EFY.
Position
Kueski is seeking a Principal Software Engineer to own technical strategy across Kueski Pay, Kueski Cash, and the shared platforms behind them, reporting to the CTO. This role is ideal for an engineer with strong architectural judgment and a track record of setting multi-year technical direction in environments with fintech-grade expectations for reliability, security, fraud prevention, and compliance.
As a key leader, you will translate company priorities into a coherent multi-year architecture, make trade-offs explicit, and define the strategy that makes Kueski an AI-native engineering organization. You will raise the decision quality of Staff and Senior engineers and be accountable for ensuring Kueski’s systems scale with the business.
Key Responsabilities
Technical Strategy & Architecture
Define the multi-year technical strategy across domains with the CTPO and engineering and product leadership.
Set the architectural principles and standards for scalability, reliability, and maintainability across Kueski’s systems; with compliance, fraud prevention, security, and regulatory requirements built in from the start.
Turn ambiguous problems into clear proposals with explicit scope, trade-offs, and build, buy, or partner decisions.
Reduce systemic technical debt and recurring failures while improving throughput, using delivery and quality metrics (throughput, cycle time, CFR, MTTR) to guide roadmaps.
AI-Native Transformation
Own the AI-native transformation roadmap: decide what to wrap, refactor, expose, or retire so AI agents can work safely on existing systems.
Define the AI-native SDLC and the context engineering standards that make Kueski’s code, data, and business logic usable by models and agents.
Lead high-stakes AI capabilities into production with measured business impact, under governance built with Risk, Compliance, and Security.
Engineering Leadership & Influence
Set technical direction for the AI Enabling Team, and coach and sponsor Staff and Senior engineers.
Shape how Kueski hires and promotes senior engineering talent.
Communicate technical direction to executives and represent Kueski’s engineering externally.
Job Requirements
15+ years building software, with 4+ years at Staff, Principal, or equivalent technical-leadership scope across multiple teams.
Track record defining and delivering multi-year architecture for high-scale, distributed, transactional systems.
Deep expertise in distributed systems, financial domain modeling (money movement, ledgering, identity), observability, CI/CD, and cloud infrastructure.
Evidence of measurable impact on reliability (CFR, MTTR, incident reduction), cost of ownership, or delivery speed.
Several years designing and shipping ML/AI systems in production at scale, including agentic or LLM-based systems.
Familiarity with MLOps/LLMOps tooling and production observability for AI.
A point of view, backed by results, on transforming a legacy engineering organization into an AI-native one.
Preferred experience in fintech, payments, lending, or another regulated industry, with hands-on work on security, fraud, and compliance; ideally shipping AI in credit, risk, collections, fraud, or underwriting.
Experience partnering directly with C-level leaders and translating strategy into technical roadmaps.
Proven record of growing senior engineers into Staff-level leaders.
Excellent written and spoken communication in English and Spanish.
Diversity & Inclusion
At Kueski we embrace diversity in all forms, systematically promote equity, and ensure everyone feels included with a sense of belonging. We are committed to the full inclusion of all qualified candidates. As part of this commitment, we will make efforts to ensure reasonable accommodations are made during the hiring process. If reasonable accommodation is needed, please let the Talent Acquisition team know.
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