About Vymo
Vymo transforms how financial institutions manage their distribution networks and collections operations. Our AI-powered DMS and CMS platform serves 350,000+ users across 70+ global financial enterprises, enabling banks and insurers to optimize performance across their distribution channels, and empowering banks to drive operational excellence in collections.
Why Global Leaders Choose Vymo
Vymo partners with financial institutions through a comprehensive solution that combines deep domain expertise with cutting-edge technology. Our platform's human-centric design, coupled with enterprise-grade scalability and AI-powered intelligence, delivers measurable business outcomes while ensuring high user adoption and engagement.
Recognition & Trust
- Backed by $45M+ funding from Peak XV partners (formerly Sequoia), Emergence Capital, and Bertelsmann Investments.
- Trusted by leading global financial institutions including Berkshire Hathaway, AIA, AXA, SBI Life, HDFC Bank, Aditya Birla Capital, Tata AIA, ABSLI and many more!
- Recognized by Celent in their 2024 Distribution Management Solutions report, with an Advanced Functionality ranking.
- Featured in Gartner's Market Guide for Sales Engagement Applications and recognized as a
- Strong Performer in Forrester's Sales Engagement Wave Report.
- Microsoft AI for All award winner for innovation in artificial intelligence
The Role
The Engineering Support Manager builds the operating model that enables Support and Engineering to function as one team. The role owns the end-to-end lifecycle of production issues—from triage and investigation to root cause analysis, resolution, and continuous improvement.
Success in this role is about creating repeatable systems rather than solving individual incidents. You will establish the operational discipline—runbooks, escalation paths, SLAs, and RCA practices—that ensures issues are resolved consistently, efficiently, and with minimal dependency on individual expertise.
You will lead a team that combines technical depth with customer communication, partnering closely with Engineering while building confidence with enterprise customers. As Vymo expands its AI-native platform, Support operations will increasingly leverage intelligent agents to triage issues, correlate signals, recommend root causes, and automate repetitive workflows.
This role is responsible for building the operational foundation that makes that future possible. Every process, runbook, and RCA should be designed to be structured, repeatable, and AI-ready.
You are not expected to build AI systems. You are expected to build an operating model that allows AI-native support capabilities to be adopted quickly and effectively.
Please fill the form: https://forms.gle/W6JVh4hRdNABdq9L8
What You Will Do
1. Production Operations : Own the end-to-end management of production issues, ensuring timely resolution, clear customer communication, and sustainable root-cause fixes.
- Own Production Triage and Resolution: Drive the entire lifecycle of complex production issues spanning the support-engineering boundary from initial triage through final resolution.
- Architect Root Cause Frameworks: Build automated severity frameworks and lead blameless root cause analyses that permanently alter system behavior to prevent failures.
- Govern SLA and Pattern Telemetry: Define realistic operational SLAs and use ongoing issue telemetry to proactively resolve recurring failure patterns before they impact retention.
2. Build Operational Excellence — Process, Runbooks, and Metrics
- Standardize Runbooks and SLAs: Maintain clear runbooks, escalation paths, and realistic SLAs so resolution doesn't depend on any one person.
- Run Blameless RCAs: Ensure every major incident gets a root cause analysis with a clear, tracked fix.
- Track Metrics and Improve Continuously: Monitor MTTR, ticket volume, and recurrence rate to catch patterns and drive process improvements
3. Lead and Develop a Team: Capable of partnering effectively with both Engineering and enterprise customers.
- Cultivate Hybrid Technical Talent: Recruit and scale an elite team pairing architectural depth with clear client-facing communication.
- Enforce Rigorous Technical Bars: Establish and coach the team against definitive excellence benchmarks for production triage.
- Reframe Escalations as Insights: Foster an operational culture that treats escalated issues as learning data for engineering.
- Establish Genuine Growth Tracks: Define clear, high-status career paths moving toward deeper engineering or operational leadership.
4. Build for an AI-Native Support Future
- Design AI-Ready Operational Processes: Structure runbooks, triage logic, and RCA templates as explicit, programmatic workflows that an agentic system could eventually parse and execute.
- Map Human-to-Automation Transition Boundaries: Maintain a strict distinction between genuine human judgment and tasks currently done manually simply due to a lack of tooling.
- Evaluate and Integrate Emergent AI Tooling: Actively monitor and honestly assess evolving AI-native support capabilities to strategically redesign team structures around automated workflows.
What You Will Bring
Experience and Fluency
- Hands-on Engineering Foundation: 8–10 years of total experience, including direct production code delivery and 2–3 years managing the critical engineering/support interface.
- Architectural Triage Depth: Fluidly reads codebase repositories, diagnostic logs, and architecture diagrams to independently drive highly technical Root Cause Analyses (RCAs).
- Operational Process Architecture: Proven track record of designing, implementing, and measuring high-velocity runbooks, SLA metrics, and on-call escalation frameworks.
- B2B Enterprise SaaS Acumen: Deep experience managing mission-critical production incidents where software downtime carries immediate, high-stakes commercial liability for clients.
- People & Operational Leadership: Managed technical teams of 3–6 people, establishing strong technical benchmarks while actively engineering career growth tracks.
Mindset & Core Traits
- High-Agency Problem Ownership: Autonomously claims ownership of ambiguous production incidents; builds repeatable, automated workflows rather than relying on existing checklists.
- Calm Under Production Pressure: Serves as a steadying operational anchor during live, high-priority incidents, communicating flawlessly across technical and client-facing boundaries.
- Systemic, Anti-Heroic Thinker: Rejects dependencies on tribal knowledge by systematically engineering out single points of failure and mandating metrics-driven process improvements.
- Forward-Looking AI Orientation: Genuinely curious about AI-native workflows; structures operational logic today so it is inherently ready to adopt emergent autonomous triage tooling.
- Continuous Improvement Catalyst: Flourishes in dynamic evolution rather than steady-state maintenance, treating support escalations as invaluable product-feedback loops.
