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VP Engineering (Nagar)

FINVASIA CAREER · Dehradun

📅 13/08/2026
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JD - Vice President Engineering Company Details Who we are Finvasia is a global fintech company offering technology-driven financial services across trading, investing, and wealth management. What we do With a strong presence in multiple countries, Finvasia focuses on innovation, zero-cost trading solutions, and empowering users through advanced platforms and tools. Know more about us: - Website Finvasia - https://finvasia.com - https://shoonya.com - https://jumpp.finance - Follow us on LinkedIn Page - https://linkedin.com/company/finvasia - https://linkedin.com/company/shoonyadotcom - https://linkedin.com/company/jumpp-finance Vice President Engineering Job Summary We are seeking a seasoned Vice President Engineering to lead our technology organization and drive the delivery of high-performance trading systems, scalable consumer platforms, and AI-driven financial products within a fast-evolving fintech ecosystem. This role requires strong engineering leadership, deep architectural expertise, and a proven track record of building and scaling large engineering teams in high throughput, regulated, and real-time environments. The VP Engineering will play a critical role in shaping the technology vision across trading infrastructure and AI-led financial platforms, ensuring scalability, reliability, and innovation at scale. Key Responsibilities: - Define and execute the engineering strategy aligned with business, product, and ecosystem goals (trading + AI platforms) - Own the overall system architecture, ensuring low latency, scalability, security, and high availability (99.99% uptime) - Lead end-to-end product engineering lifecycle across trading systems, consumer apps, and AI platforms. - Drive engineering excellence through structured delivery governance, release management, and quality frameworks. - Manage and reduce technical debt while continuously improving system performance, latency, and reliability. - Establish and track engineering KPIs such as latency, uptime, throughput, deployment frequency, and defect rates. - Champion DevOps, CI/CD, automation, and SRE practices to ensure resilient and scalable systems. - Ensure compliance with BFSI regulatory, security, and risk standards, especially for trading and financial data systems. - Lead the architecture and execution of AI/ML-driven systems, including personalization, recommendation engines, and conversational AI. - Build, lead, and scale high-performing, multi-disciplinary engineering teams across backend, frontend, mobile, data, and AI. - Collaborate closely with Product, Business, Data Science, Risk, and Compliance teams for aligned execution. - Drive org design, hiring, leadership development, and succession planning across engineering functions. - Manage engineering budgets, vendor ecosystem, and technology investments. - Define long-term technology roadmap, including adoption of AI-first, event-driven, and cloud-native architectures Experience & Qualifications - 18+ years of engineering experience with 5+ years in senior leadership roles (VP/Director/Head of Engineering) - Strong experience in Fintech / Trading platforms / High-scale consumer tech ecosystems. - Experience in product-based organizations or high-growth startups. - Proven experience in designing and scaling high-volume, low-latency, transaction-driven systems. - Hands-on experience with: - Backend technologies: Java (preferred), microservices, distributed systems architecture. - Frontend technologies: Contemporary JS frameworks (React/Angular/Vue) - Mobile development: Android/iOS platforms - DevOps & SRE: CI/CD, containerization (Docker/Kubernetes), monitoring & observability. - Streaming systems: Kafka / real-time event processing (preferred) - Demonstrated experience in building and managing large cross-functional engineering teams including backend, frontend, mobile, data, and QA teams. - Experience working in regulated, security-driven environments (BFSI/trading systems). - Strong understanding of engineering metrics, release governance, system reliability, and performance optimization. .
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