Customer Support Engineer

Blitzy•Cambridge, MA

3d•Onsite

About The Position

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into production-ready code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Requirements

Distributed-systems debugging. Reason about a request crossing multiple services, queues, and network hops, and isolate which hop failed. You debug by forming a hypothesis and confirming it with evidence (logs, pod state, queue depth, DB rows), not by guessing.
Kubernetes & Docker.
Major cloud providers: GCP, AWS, and Azure. Hands-on with at least one deeply and able to work across the others: managed Kubernetes (GKE/AKS), cloud logging, IAM/auth basics, and cloud disk/storage behavior.
Strong monitoring & observability practice. Fluent with an APM/observability stack (Datadog or equivalent): log queries, correlating across services by request/trace IDs, reading traces, and building dashboards and alerts. You reach for the data before theorizing.
Methodical, evidence-first temperament. Hold several candidate causes at once, run the cheapest disconfirming check first, and never claim a root cause or fix you haven't proven.
Multi-tenant safety mindset. Environments are shared and customer-owned: default to read-only diagnostics and understand blast radius before changing anything.

Nice To Haves

Python and Redis literacy.
Basic message queueing. Command transport runs over a message queue (Redis/rq). Comfort inspecting queue depth, backlogs, and stuck/failed jobs; concepts transfer from any broker.
Networking & WebSockets. Many of our hardest issues are connection problems: WebSocket/ Socket.IO drops, NAT/idle/LB timeouts, half-open sockets, DNS-vs-routing, TLS. Tell a transport fault from an application fault.
SQL / PostgreSQL. Query operational tables to confirm what the system recorded.
Source-control platforms. GitHub (incl. GitHub Enterprise Server), Azure DevOps, and/or GitLab, clone/push/pull, access tokens, app credentials, and their failure modes.
CI/CD, Helm & deploy integrity. Many "sudden regressions" are a bad or partial deploy: check what version is actually running before chasing architecture theories. Helm and container deploy pipelines expected. ArgoCD is a plus.
Secrets management. Comfort handling secrets, credentials, and certificates safely, ideally with Vault (strongly preferred).
Linux and Windows. Workloads run on both; comfort triaging on each OS (process inspection, filesystem, basic networking).
Incident management & ticketing workflows: Jira or similar (a plus).
Prior customer-facing support or SRE/on-call experience (a plus).

Responsibilities

Deploy and install the platform into customer environments, and troubleshoot installation issues.
Support ongoing upgrades and day-to-day operation, keeping customer environments stable.
Work alongside L1 to triage and resolve customer-reported issues, driving them to resolution or escalation.
Diagnose failures across the stack: compute, networking, storage, and the services running on it.
Reproduce issues safely against live (often multi-tenant) environments using read-only diagnostics first.
Build and maintain dashboards, monitors, and runbooks so recurring issues get faster to fix: or stop recurring.
Write up clear, evidence-backed escalations and post-incident notes.
Communicate status and resolution to customers clearly and on time.