Technical Support Engineer - L2

Accountabilities

• Own escalated technical support cases end-to-end, including investigation, root-cause analysis, resolution, customer confirmation, and accurate case closure.

• Troubleshoot complex issues across conversational AI flows, voice integrations, REST APIs, webhooks, core banking connectors, and other integrated systems.

• Identify and categorize AI behavior issues such as hallucinations, intent misclassification, knowledge gaps, flow configuration problems, and integration failures.

• Use logs, call recordings, digital transcripts, API traces, dashboards, and observability tools to diagnose production issues and identify underlying causes.

• Analyze escalated AI conversations and provide sufficiently detailed root-cause insights for ML and Product teams to take corrective action.

• Create, refine, and retire knowledge base content to improve AI resolution rates and continuously strengthen customer-facing experiences.

• Communicate directly with customer technical and operational stakeholders through email and calls, providing clear updates and managing expectations throughout the resolution process.

• Manage escalated tickets in Salesforce Service Cloud, ensuring timely acknowledgment, appropriate prioritization, resolution, and audit-ready documentation.

• Lead P1 and P2 incident response activities, including war room coordination, timestamped updates, and parallel communication with Engineering and customer teams.

• Prepare detailed post-mortems covering incident timelines, root causes, customer impact, resolutions, and preventive actions, including documentation suitable for leadership and compliance review.

• File actionable bug reports that provide Engineering with sufficient information to investigate and resolve issues without unnecessary follow-up.

• Identify recurring technical and AI behavior patterns and translate them into structured insights for Product and ML teams.

• Escalate compliance-sensitive issues promptly, including concerns related to call recordings, disclosure language, and member data.

• Maintain ownership of assigned queues, prioritize competing issues effectively, and independently drive cases to resolution.

Requirements:

• Bring 5+ years of experience in technical support, implementation support, or a similar customer-facing technical role within a B2B SaaS environment.

• Demonstrate strong hands-on experience debugging REST APIs and webhooks, including authentication failures, integration traces, and event-driven architectures.

• Have practical experience with PostgreSQL or SQL for querying session data, analyzing usage patterns, and validating data integrity across integrated systems.

• Be comfortable using Python for diagnostic scripts, log parsing, troubleshooting, and lightweight internal tooling.

• Have experience with observability platforms such as OpenSearch, Kibana, Grafana, Datadog, or equivalent tools, including queries, dashboards, and distributed traces.

• Understand voice technology concepts such as SIP and IVR routing and be able to distinguish ASR-related issues from AI model behavior.

• Have experience using Salesforce Service Cloud or a comparable case-management platform for escalation tracking, documentation, and audit trails.

• Familiarity with Kubernetes, including reading pod logs, understanding deployment states, and navigating cluster context during incident investigations, is an advantage.

• Bring hands-on experience with AI agent creation and orchestration, including agent configuration, tool chaining, guardrails, and debugging multi-step workflows.

• Be proficient with modern AI-assisted development and investigation tools such as Cursor and Claude Code, using them effectively for codebase exploration, troubleshooting, and scripting.

• Be able to critically evaluate AI conversation transcripts across voice and digital channels and identify meaningful quality or behavioral issues.

• Demonstrate excellent written and verbal communication skills, with the ability to work effectively with both technical and non-technical customer stakeholders.

• Produce precise, audit-ready documentation that allows anyone reviewing a case to understand the situation, investigation, decisions, and outcome.

• Demonstrate high agency, strong judgment, and a proactive approach to resolving issues without waiting for detailed direction.

• Be highly self-directed and capable of independently managing a technical support queue in a fast-paced environment.

• Demonstrate strong ownership, organization, problem-solving ability, and the resilience required to manage business-critical incidents.

Benefits:

• Remote-first working environment with the flexibility and autonomy associated with a distributed team.

• Opportunity to work at the forefront of generative AI and conversational AI within the financial services industry.

• High-ownership role with significant autonomy over complex technical investigations and customer outcomes.

• Exposure to advanced AI agent orchestration, APIs, integrations, observability, cloud technologies, and enterprise SaaS environments.

• Opportunity to directly influence AI quality by turning production support cases and customer interactions into actionable improvements.

• Collaboration with Engineering, Product, ML, and customer teams on technically challenging problems.

• Comprehensive benefits package.

• Opportunity to develop expertise in AI-powered customer service and enterprise financial technology.