Codemonk Handpicked

Hire engineers who've shipped it before.

Pre-vetted engineers and AI specialists, matched to your stack and your outcomes. First shortlist in about a week — no hiring pipeline to run.

See how it works
1 weekto first shortlist
250+engineers placed since 2022
80%interview-to-hire ratio
AS
Ananya Suresh
Backend Engineer
6+ yrs
GoPostgreSQLKafka
Available now
RK
Rohit Kapoor
AI / ML Engineer
5+ yrs
PyTorchLangChainRAG
MP
Meera Pillai
Frontend Engineer
4+ yrs
ReactTypeScriptNext.js
Available · Sep 12

Engineering teams building with Handpicked

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Why Handpicked

Skip the recruitment maze.

Onboarding Time
Often weeks of back-and-forth before a single candidate
First shortlist in about a week
Precision Matching
Resume-keyword matching — you find out if they're qualified in your own interview
Structured technical evaluation before you ever see a profile
Employee Overheads
Standard employment overheads if hired direct
No ESOPs, no severance — engineers stay on our payroll
Training
Generic sourcing; training often falls on you
Pre-vetted for the exact stack you need
Scale Flexibility
Rigid contracts — hard to swap or exit
Scale up, down, or convert to hire, on your terms

What we ship

Engineers matched to what you're building.

01

Core Product Engineering

A roadmap slows down the moment there aren't enough hands to build it in parallel.

Backend, frontend, and full-stack engineers who embed into your existing team and ship in your codebase from week one.

Matched to your stack and your team's way of working.
02

Mobile Engineering

Your product doesn't stop at the browser.

iOS, Android, and Flutter engineers who ship native and cross-platform experiences without slowing down your core roadmap.

Matched to your platform and your release cadence.
03

QA / Quality Engineering

Shipping fast only works if it doesn't break in production.

QA and SDET engineers who build test coverage and catch what manual review misses, embedded in your release cycle.

Matched to your test coverage gaps, not a generic checklist.
04

AI & Applied ML

Most AI prototypes stall between a working demo and a system that survives production traffic.

AI and applied ML engineers who take models from notebook to production — with the evals, observability, and failure handling that make them dependable.

Matched to your model, your data, and your production constraints.
05

Data Platforms

Data lives across a dozen systems, and nobody fully owns turning it into something usable.

Data engineers who build the pipelines, warehouses, and activation layers a business runs its reporting and product decisions on.

Matched to your pipeline and your existing data stack.

Building across more than one of these? Tell us what you're working on — we'll match the right mix.

How it works

From scoping call to shipped code.

01

Tell us what you're building.

A 30-minute call on your stack, roadmap, and team dynamics — enough for us to match engineers to what you actually need.

02

Meet engineers who've done it.

Every candidate gets a structured evaluation — technical depth, system design, communication — from senior engineers or an AI interviewer for select roles. It's a final read, not a discovery call.

03

They embed and ship.

One engineer or a full squad, working in your repo, your tools, and your standards from day one — no ramp-up, no separate onboarding process to manage.

04

We stay in the loop.

Regular check-ins keep the engagement on track, and if the fit isn't right, we move quickly to replace — no drawn-out process on either side.

Engagement models

How you bring in Handpicked engineers.

Default engagement

Contract

The way most teams bring in Handpicked engineers. Pre-vetted talent — one engineer, or a composed team — who join your roster and work under your direction from day one.

Best for
  • Release sprints and capacity spikes
  • Specialized stack coverage
  • Multi-role teams sized to the work — a 3-person data engineering team, a BA + backend engineer + QA squad for an integration project, or a single senior hire
  • Short-to-long-term engagements
Contract-to-hire (C2H)Built into every Contract. Bring an engineer onto your own payroll when you're ready — conversion terms are pre-agreed upfront during scoping.

What we handle

Focus on the work. We handle the rest.

Engineers on Codemonk's payroll

A variable cost, not a fixed liability — no entity setup, no contractor paperwork, no ESOPs or severance to negotiate.

Payroll, statutory compliance, and contracts handled

Salary runs, tax filings, and every statutory requirement are managed on our end, start to finish.

NDA, IP transfer, and background verification built in

Every placement ships with signed NDAs, clean IP assignment, and a completed background check — before day one.

Replace or convert anytime

If a placement isn't right, we replace it. If it's a fit, converting to your own payroll is a straightforward next step — you're never carrying the risk alone.

Onboarding and equipment ready before day one

Laptops, access, and orientation are sorted ahead of the start date, so the engineer is writing code on day one, not filling out forms.

Industries

Industries we've shipped in.

From regulated markets to high-growth platforms — engineers matched to the domain, not just the stack.

Banking, Fintech & Insurance

Payments, claims, underwriting — engineers who've shipped inside regulated, audit-heavy environments before, not just read about them.

SaaS

Product engineers who've built and scaled multi-tenant platforms — not maintained one, built one.

Healthtech & Healthcare

Clinical workflows, patient data, compliance-heavy builds — engineers who don't need a crash course in HIPAA before they're useful.

Retail & E-commerce

Catalog, checkout, fulfillment under real load — engineers who've handled peak-traffic days, not just steady-state ones.

Logistics & Supply Chain

Routing, tracking, warehouse systems — engineers who've worked where downtime has a real operational cost, not just a support ticket.

Across the stack

Engineers across the stack.

AI / MLLLMs · MLOps · Applied AI
Backend EngineeringGo · Java · Node · Python
Frontend EngineeringReact · Next.js · Vue
Data EngineeringSpark · Kafka · dbt
Mobile EngineeringReact Native · Flutter · iOS/Android
AI / MLLLMs · MLOps · Applied AI
Backend EngineeringGo · Java · Node · Python
Frontend EngineeringReact · Next.js · Vue
Data EngineeringSpark · Kafka · dbt
Mobile EngineeringReact Native · Flutter · iOS/Android
DevOps & CloudAWS · GCP · Kubernetes
QA / SDETAutomation · Performance
MERN StackMongo · Express · React · Node
MEAN StackMongo · Express · Angular · Node
Platform EngineeringInternal tooling · Infra
DevOps & CloudAWS · GCP · Kubernetes
QA / SDETAutomation · Performance
MERN StackMongo · Express · React · Node
MEAN StackMongo · Express · Angular · Node
Platform EngineeringInternal tooling · Infra

If your stack isn't listed, ask — we move quickly into adjacent areas when the need is real.

In their words

Teams who'd bring us in again.

It's been an absolute pleasure working with Codemonk over the past few years. They have been instrumental in our journey of building Appsmith. Their proficiency in React and web app development was evident as they meticulously helped us build the platform. I highly recommend Codemonk for building React based applications.
Arpit Mohan
Arpit Mohan
Co-founder, Appsmith
Our experience with Codemonk has been truly exceptional at Insureka!. They not only met our expectations but consistently surpassed them. In a span of just seven months, Codemonk's talent has played a pivotal role in our mission to digitalize the process of selling automobile insurance in the highly competitive Indonesian market.
Darshan Sonde
Darshan Sonde
CTO, Insureka!

FAQ

Questions that usually come up.

What are you trying to ship?

Tell us about the capability you need. We'll match engineers who've shipped it before — usually within a week.

Explore engagement models