Lead Software Engineer

• Enforce and evolve best engineering practices:  

• Clean, maintainable, and testable code  

• Strong code reviews (PR ownership and guardrails)  

• CI/CD, automation, and observability  

• Performance, scalability, and security best practices  

• Experience with event-driven architecture  

• Exposure to AI-assisted development workflows  

• Prior experience working in high-scale, client-facing platforms 

Technical Leadership & Delivery 

• Lead end-to-end design and delivery of scalable, high-performance applications 

• Lead development and maintenance of both live production systems and legacy applications, ensuring stability while progressively modernizing the platform 

• Balance business continuity with technical evolution, reducing technical debt without impacting client delivery  

• Own system architecture decisions across frontend, backend, and data layers  

• Drive full-stack development with strong focus on backend (Java) and modern frontend frameworks  

• Ensure systems are resilient, observable, and production-ready 

Quality Ownership & Shift-Left Mindset 

• Champion a shift-left engineering approach, where quality is owned by engineers from design to production  

• Ensure features are built with testability, observability, and validation in mind from day one  

• Drive practices such as unit testing, integration testing, and automation as part of development—not post-development  

• Eliminate dependency on downstream QA by embedding quality checks within the development lifecycle  

• Foster a culture where engineers are accountable for the correctness and reliability of their code in production 

Squad Leadership & Mentorship 

• Lead a squad of engineers (junior to mid-level), providing technical guidance and mentorship  

• Set clear expectations on delivery, code quality, and ownership  

• Actively coach engineers to improve design thinking, coding standards, and debugging skills 

Product & Stakeholder Collaboration 

• Partner closely with Product Managers to understand business priorities and translate them into clear technical execution plans  

• Drive clarity in requirements, scope, and trade-offs  

• Ensure alignment between business goals and engineering outcomes 

AI-Enabled Development 

• Leverage AI tools (e.g., company approved coding assistants) to improve productivity and speed  

• Ensure thoughtful and responsible usage—not blind reliance  

• Guide the team in using AI for the right problem statements (automation, acceleration, not shortcuts) 

Ownership & Accountability 

• Take end-to-end ownership of systems and deliverables  

• Be accountable for delivery timelines, quality, and production stability  

• Proactively identify risks, resolve blockers, and drive outcomes without dependency 

• Contribute to internal knowledge sharing through documentation, technical talks, or workshops.  

• Showcase delivery outcomes and business impact to stakeholders through clear, structured, and data-driven communication.