• Lead day-to-day engineering execution in a hands-on management capacity, ensuring priorities, ownership, timelines, risks, dependencies, and quality expectations are clear. • Manage Web Services engineers and contractors, including coaching, feedback, prioritization, performance support, and team development. • Manage team budget and resource planning, including contractor, vendor, tooling, service, operational expense, and headcount planning inputs. • Translate product direction, technical priorities, and organizational needs into coordinated engineering plans. • Establish team processes, workflows, planning practices, and operating rhythms that improve clarity, accountability, quality, and predictability. • Maintain enough product and architectural context to evaluate tradeoffs, identify risks, and manage engineering work credibly. • Improve engineering practices related to code review, testing, documentation, release readiness, observability, technical debt, and operational readiness. • Coordinate launch and operational readiness across technical and cross-functional partners. • Communicate progress, priorities, risks, and decisions clearly to stakeholders while fostering an engineering culture grounded in accountability, inclusion, technical quality, open-source values, and continuous improvement.

• Partner with EMs across Virta to proactively solve their delivery friction, establish structured feedback loops with product teams, and align on win-win adoption strategies that drive capability utilization without sacrificing product timelines. • Drive continuous process optimization with a specific focus on AI-native development. Partner with the team to safely experiment with agentic coding tools, reducing development toil and improving cycle times while preserving team expertise, technical skills, judgment, and domain knowledge. • Own the technical strategic vision for Virta’s core platform capabilities. Partner with product and engineering leaders to ensure the architecture scales to meet future business goals, balancing quick-win acceleration bets with long-term investments. • Lead and support a senior-leaning, autonomous squad, fostering a high-ownership environment built on trust. Act as a strategic facilitator and decisive tie-breaker when senior team members face complex technical decisions. • Focus deeply on senior talent development. Create growth paths that challenge experienced engineers to scale their impact from "problem solvers" to "system thinkers," coaching them on navigating organizational influence and progressing toward Staff/Principal levels.

Role Description We're hiring an Engineering Manager to lead a team of backend/full-stack engineers building and operating production systems at real scale. You'll own delivery end to end — from technical strategy through execution — while staying hands-on enough to review code, unblock your team, and contribute when it matters. This is a role for someone who wants to keep growing as both a technical leader and a people leader, in a company that's genuinely figuring out how to use AI well, not just talking about it. - Lead a team of engineers building and operating production systems — owning delivery, quality, and cost. - Shape technical strategy in collaboration with your team and other leaders, balancing long-term architecture with near-term pragmatism. - Drive projects end to end: scoping, sequencing, estimation, execution, and post-launch ownership. - Set the engineering bar for your team — code review culture, testing discipline, observability, security, and responsible AI use. - Hire, develop, and retain strong engineers; give them work that stretches them and feedback that lands. - Set a clear technical direction and help your team understand not just what you're building, but why. - Represent your team's work through clear written updates and well-run forums. - Help define what "good" AI-assisted engineering looks like on your team — and coach others toward it. Qualifications - 6–9 years of experience building production software, including roughly 2+ years directly managing engineers (not just a tech lead role). - A track record of shipping non-trivial systems end to end and operating them in production at meaningful scale. - Real, hands-on experience using AI tools to improve how you and your team build software — you can speak to what works, what doesn't, and why, with genuine enthusiasm. - Experience hiring engineers and raising a team's bar over time, including handling underperformance. - Clear, structured written and verbal communication — comfortable working async with a distributed team. Requirements - Experience in fintech, lending, payments, KYC, or credit underwriting. - Familiarity with Ruby on Rails — or strong backend fundamentals in Java, Python, or Node.js with the appetite to ramp up quickly. - Experience working across systems of meaningfully different scale or complexity. - Prior experience at both smaller, fast-moving teams and larger, process-mature organizations. Benefits - Competitive compensation, plus equity. - 100% remote — work from anywhere in India. - Fully paid group medical and personal accident insurance. - Generous paid time off plus public holidays. - Fully paid parental leave: 12 weeks for fathers/non-birthing parents, 26 weeks statutory maternity leave. - Monthly WFH stipend plus a one-time home office setup budget. - $500 annual professional development budget. - Quarterly social meet-ups and sponsored monthly team lunches.

• Lead engineering teams responsible for data ingress, pipelines, datalake adoption, Data APIs, permissions, and data access interfaces. • Own execution and technical direction across Rockerbox’s data foundation and customer-facing data access layers. • Ensure reliable, timely, and scalable client data delivery. • Align ingestion, aggregation, API access, permissions, and AI-enabled data workflows under clear ownership. • Partner with Product, Applications, Integrations, Data Science, Customer Success, and DV stakeholders on platform strategy. • Enable internal teams and customers to access Rockerbox data through APIs, CLI tooling, and future agentic workflows. • Improve team efficiency through automation, reduced maintenance burden, and clearer ownership. • Manage, develop, and retain engineers through a period of organizational transition. • Reduce bottlenecks between Data, Applications, and customer-facing product development.