Tech Lead Application Infrastructure

About Payoneer

Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.

By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.

Role summary 

As a Tech Lead on our Application Infrastructure team, you will own the technical direction, architecture, and evolution of the core platform components that power Payoneer's global financial services. 

You'll work on highly available, distributed systems that serve millions of customers across 190+ markets, partnering with engineering teams to deliver shared frameworks, libraries, and cloud-native services. This is a role for someone who genuinely loves technology, is energized by AI's impact on how we build software and wants to shape the foundation that the rest of engineering builds on. 

Location: Gurugram, India Hybrid 

What you’ll do 

• Provide technical leadership and architectural direction for backend systems serving Payoneer scale, scalability, performance, security, reliability, and cost. 


• Lead by example in hands-on development, own critical code paths, tackle the hardest problems, and set the standard for code quality on the team. 


• Own technical design decisions for your domain, lead design reviews, author and review ADRs/RFCs, and design data models and high-performance access layers across SQL and NoSQL stores with explicit attention to schema evolution, query patterns, and scale. 


• Partner across Product, Architecture, Security, SRE, and DevOps to define APIs, contracts, and shared platform capabilities that other engineering teams depend on every day. 


• Own backend reliability and performance outcomes, define and uphold SLOs, lead incident response on critical paths, treat observability as a design property (golden signals, structured logging, tracing, actionable alerts), and drive measurable improvements in latency, error-budget burn, and infrastructure cost. 


• Champion a security-first and compliance-aware engineering posture, PCI DSS, PII handling, multi-tenant isolation, secrets management, and secure-by-default patterns are non-negotiable. 


• Set and uphold the organisation's standards for AI-assisted development, context engineering, prompt and instruction patterns, AI code review protocols, and safe-use boundaries (what can be AI-generated, what requires human design, what must never leave our boundary, and how AI-assisted changes are reviewed, attributed, and audited). 


• Own and evolve the internal AI tooling playbook, Cursor IDE, Claude Code, Codex CLI, and the next wave, including evaluation of emerging AI coding tools with adoption recommendations grounded in measured trade-offs across developer velocity, code quality, security posture, cost, and lock-in risk. 


• Measure the impact of AI-augmented engineering, establish baselines and track outcomes so adoption decisions are evidence-based, not anecdotal. 


• Raise the engineering bar across the team, contribute to hiring and calibration, and drive improvements in engineering processes, tooling, and quality standards (CI/CD, testing strategy, developer experience). 

Who you are 

• 10+ years of professional backend software development experience, with a track record of leading technical direction across complex, distributed systems serving production scale. 


• Demonstrated experience leading platform-building efforts end-to-end, from design through production rollout. 


• Track record of driving tooling, process, or technical-standard adoption at team or org scale, with measurable productivity or quality outcomes. 


• Strong proficiency in a strictly typed language, here, primarily C# and .NET. 


• Hands-on experience with cloud infrastructure on AWS (preferred) or Azure, including production use of Docker and Kubernetes. 


• Proven experience with both SQL databases (SQL Server, PostgreSQL, MySQL) and NoSQL stores (MongoDB, Redis, DynamoDB, or Cosmos DB), schema design, query optimization, and scaling. 


• Solid grounding in distributed systems patterns, microservices, asynchronous messaging, caching, resiliency, idempotency, and REST/event-driven API design, and comfortable owning reliability, performance, and cost outcomes. 


• Hands-on experience building AI-based products or features, integrating LLMs, AI APIs, or AI coding assistants into real software, with genuine curiosity about applying AI to platform and infrastructure problems. 


• Demonstrated fluency with modern AI coding tools (Cursor, Claude Code, Codex CLI, Copilot, or equivalents). 


• Solid understanding of data structures, algorithms, and system design trade-offs; test-oriented approach to engineering. 


• Decisive leader and strong communicator, drives clarity, makes informed decisions, and produces crisp design docs, RFCs, and postmortems for both technical and non-technical audiences. 


• Builder's mindset and team player, curious, pragmatic, transparent, and invested in the growth of the engineers around you. 

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