Director, Engineering

Role overview

Director, Engineering at Magnit Global

Responsibilities

• You'll set technical direction, raise the engineering bar, and partner closely with Product, Operations to ship outcomes that customers feel.
• Build with AI, not around it.
• Drive measurable reduction in manual work and meaningful lift in operational accuracy.
• Drive excellence across architecture, code quality, testing, CI/CD, observability, security, and release management.
• Build the culture.
• Develop the next layer of engineering leaders under you.
• Track record of leading teams that built and scaled enterprise SaaS platforms, VMS, workforce management, procurement, FinOps, HR Tech, or workflow automation.

Employment details

• Location: Bengaluru [Karnataka] [India]

About the employer

• As Director of Engineering for Operations & AI Automation, you'll own the engine room of the Magnit Global VMS platform, the systems that power clients, suppliers and workers with intelligent workflows, and the data layer underneath.

Additional role details

• You'll lead 3–4 teams building agentic capabilities, automation, and insights that turn manual operational work into product.
• This is both hands-on-the-keyboard, hands-on-the-strategy role for a leader who has shipped real AI into production, not slideware, and who knows the difference between a demo and a system that large number of enterprise users depend on at 9am Monday.
• What you'll do Lead the org.
• Manage and grow 3–4 engineering teams across the product line.
• Hire, coach, and develop managers and senior ICs.
• Set technical direction.
• Own architecture, delivery priorities, and engineering standards across your teams.
• Make the trade-offs that matter, build vs. buy, speed vs. reliability, automation vs. headcount.
• Ship production-grade AI agents, RAG systems, workflow orchestration, and tool-calling capabilities.
• Turn operations into product.
• Partner with Product, Operations to convert recurring operational pain into reusable platform capabilities, anomaly detection, intelligent reporting, decision support, automated workflows.
• Raise the engineering bar.
• Improve delivery predictability and platform reliability quarter over quarter.
• Use data as a product asset.
• Mine platform data for risk signals, efficiency gaps, and product opportunities.
• Make data-driven prioritization the default, not the exception.
• Plan capacity, ruthlessly.
• Balance roadmap delivery, automation investment, technical debt paydown, and innovation across teams.
• Defend the long-term while shipping the quarter.
• Establish clear ownership, high standards, and a high-performance, low-drama team culture.
• What you'll bring 10+ years of engineering experience, including 5+ years leading engineering teams (managers reporting to you is a plus).
• Practical, production experience with AI agents, GenAI, RAG, agent orchestration, tool-calling, and AI evaluation.
• You've shipped this in front of real users, not just prototyped it.
• Strong fluency in cloud platforms (AWS), microservices, APIs, event-driven systems, DevOps, and observability.
• Demonstrated ability to improve engineering quality, delivery predictability, platform stability, and team performance and the metrics to prove it.
• Strong product mindset.
• You connect technology decisions to customer value and business outcomes, and you push back when the math doesn't work.
• A track record of hiring, developing, and retaining strong engineering talent, including managers.
• Nice to have Domain depth in worker engagement, vendor/staffing operations, or enterprise workflow automation.
• Experience shipping analytics, dashboards, anomaly detection, recommendation engines, or conversational insights at scale.
• Experience operating global, multi-region platforms across diverse customer segments.