Practice Pitches

Hi, I'm [name] — a backend engineer with [X] years in Node.js and the last [Y] focused on NestJS and TypeScript. I build and scale APIs and services.

Most recently I [shipped / owned] [a service or domain] — [one concrete thing: e.g. an auth service, a payments pipeline, a GraphQL API] — handling [scale: e.g. a few thousand RPS], with a focus on clean module boundaries, testing, and observability.

I'm drawn to this role because it's senior, backend-focused, and NestJS at its core.

I'm [name], a backend / full-stack engineer with [X] years in JavaScript and TypeScript, the last [Y] building services in NestJS on Node.

What I do well: I design modular, testable services — clear module boundaries, dependency injection, validated DTOs — and I care about what happens after deploy: structured logging, tracing, graceful shutdown, and not blocking the event loop. I'm comfortable across the data layer (Postgres with TypeORM/Prisma, Redis), auth (JWT + RBAC), and async work (queues, events).

A recent highlight: [a specific project — what it did, your role, and one measurable result, e.g. cut p99 latency by 40% or shipped a microservice that handles N events/day].

I'm looking for a senior backend role where I can own architecture and raise the team's bar — which is exactly what this looks like.

Start at the arc, not the resume. [I started in [frontend/full-stack], moved to backend because I liked owning the data and the contracts.]

Then 2–3 chapters, each one sentence of context + one thing you're proud of: “At [company] I [built X], which taught me [Y].” Show a progression — more ownership, bigger systems, more impact.

Land on the present: “Now I'm strongest at [DI-driven service design / performance / distributed systems], and I want a role where I [own architecture / mentor / scale a platform].” Tie it back to this job.

Express is great but unopinionated — large apps drift into spaghetti. NestJS gives me structure and dependency injection on top of Node's HTTP layer, so the architecture is consistent and testable from day one.

Concretely: the module system enforces boundaries, DI makes everything mockable, and the request pipeline — guards, interceptors, pipes, filters — gives me clean places for auth, validation, and cross-cutting concerns. And because it's TypeScript end-to-end, the compiler catches whole classes of bugs.

It scales from a modular monolith to microservices without changing the programming model — that's rare and valuable.

Three honest reasons, tailored: (1) the problem — [what they're building and why it's interesting to you]; (2) the technical fit — [their stack/scale matches what I do: NestJS, [their data stack], [their scale]]; (3) the role — [senior ownership / the team / remote / the domain].

Close with a forward-looking line: “I'd want to spend my first weeks understanding [their core service] and finding where I can add leverage fastest.”

Two things define Nest: dependency injection and the request lifecycle.

DI: classes declare what they need in the constructor, and the IoC container provides it. The type is the token; at bootstrap Nest builds the dependency graph and instantiates bottom-up, caching singletons. That's why everything is loosely coupled and trivially mockable in tests.

The lifecycle: a request flows through middleware → guards → interceptors → pipes → the handler → interceptors again → exception filters. Each has a job — guards do authorization, pipes validate and transform, interceptors wrap the handler for things like caching and timeouts, filters shape errors. Knowing that order lets me put each concern in exactly the right place.

Situation: [an endpoint / service] was [slow / timing out] under load — [p99 jumped to X / it fell over at Y RPS].

Task: I owned finding and fixing the root cause without a rewrite.

Action: I measured instead of guessing — [checked event-loop lag / read traces / captured a flamegraph] and found [the cause: an N+1 query / blocking CPU work / a missing index / unbounded concurrency]. I [batched the query with a DataLoader / moved the work to a worker thread / added the index / bounded concurrency], and added [a cache / a regression test].

Result: [p99 dropped from X to Y / throughput Nx'd], and I added an alert on [loop lag / p99] so it can't silently regress.

Situation: we had to [choose between X and Y — e.g. monolith vs microservice, SQL vs NoSQL, sync vs queue].

Task: I had to make the call and get the team aligned.

Action: I framed it by the constraints that actually mattered — [scale, consistency, team size, deadline] — and named the trade-off explicitly: “[option A] buys us [benefit] at the cost of [downside].” I [prototyped / benchmarked / wrote a short ADR] and recommended [the choice], with a fallback if [assumption] proved wrong.

Result: [outcome], and because I'd documented the trade-off, we didn't relitigate it later.

Node runs your JavaScript on a single thread. Think of one chef in a kitchen: they can start many dishes (network calls, file reads) and let the ovens (the OS and a small thread pool) cook in the background, checking back when something's ready. That's why Node handles thousands of slow I/O operations at once.

The catch: if the chef stops to chop a mountain of vegetables by hand — a heavy CPU task — every other dish waits. That's blocking the event loop. So we keep CPU-heavy work off that thread: worker threads or a queue.

That single mental model — great at waiting, bad at grinding — explains most Node performance advice.

Always have 3–4 ready. Good ones signal seniority:

“What does the service architecture look like today — modular monolith, microservices, somewhere in between — and what's the biggest pain point?”

“How do you handle testing, CI/CD, and observability? What's the on-call story?”

“What would success in this role look like in the first 90 days?”

“Where is the codebase paying down tech debt, and where would I have the most leverage early?”