OctogleHire
Vetted Python engineers, AI-native

Hire senior andproven Pythonengineers

Backends, pipelines and ML systems that run in production. The top 4% of applicants, scored on real code and ready to start in days.

Teams shipping with Octogle Hire
Beekey
Hireflow
Corpwise
Solidus
SquareLogik
Unichats
DNO Investments
The Care App
Workchats
Beekey
Hireflow
Corpwise
Solidus
SquareLogik
Unichats
DNO Investments
The Care App
Workchats
Your shortlist, previewed

Pick the Python problem. See who we would send.

38 matching engineers · updated hourly
Karthik NairSenior Backend Engineer94/ 100
StackFastAPI, Postgres, CeleryOwnedCore API, 120 endpointsOverlap4h with UK hours
Bengaluru · UTC+5:30$32/h
Youssef BenaliBackend Engineer90/ 100
StackDjango REST, RedisOwnedMulti-tenant billingOverlapFull UK day
Casablanca · UTC+1$31/h
Artem LysenkoEngineer87/ 100
StackPython, SQLAlchemyOwnedReporting serviceOverlap6h with UK hours
Odesa · UTC+3$25/h
The funnel

25,000 applied. 1,000 got in.

Five scored stages, all finished before a profile reaches you. Nobody skips a stage to hit a deadline.

25,000remain
Stage 01Application reviewRead by an engineer, not a keyword filter.
10,000remain
Stage 02HR + communication screenLive English fluency and product-mindset interview.
4,000remain
Stage 03AI-led Python interviewA 30–50 minute adaptive interview tuned to the CV.
1,600remain
Stage 04Tech lead interviewSystem design and production judgement, face to face.
1,000remain
Stage 05References + backgroundTwo calls with former leads, plus verification.
What it costs

From £15 an hour. That is the whole pricing page.

One hourly rate with our margin printed on every invoice, billed monthly. No placement fee and no notice period beyond two weeks.

What are you looking for?Rates shown in your currency, compared with hiring locally.
Hiring with Octogle£2,598to£5,716/ monthEquivalent to £15–£33 an hour
Save up to £68,587 a yearAll expenses included. No hidden costs.
Hiring locally in United Kingdom£8,314/ monthEquivalent to £48 an hour
45% higher annual costBased on loaded local cost, including employer on-costs.
Indicative only — your quote is confirmed on the brief call.
The role

What a Python engineer does

Python engineers design, build, test, and operate backend services, APIs, data pipelines, automation, and integration layers. In a modern stack, Python often sits behind web and mobile clients through FastAPI, Django, or Flask; powers async workers with Celery, RQ, Dramatiq, or cloud queues; connects to PostgreSQL, Redis, Kafka, and object storage; and supports AI, analytics, and platform tooling. In 2026, strong Python teams use Python 3.12 through 3.14, type hints, pytest, ruff, uv, containers, observability, and CI/CD as standard practice. A mid-level engineer can implement features from well-scoped tickets and follow existing patterns. A senior Python engineer makes design tradeoffs, models data well, prevents performance and reliability problems, reviews architecture, debugs production issues, mentors others, and knows when Python is the right tool and when it is not.

Typical responsibilities

  • Design, build, and maintain Python services, APIs, background jobs, and internal tools using frameworks such as FastAPI, Django, or Flask.
  • Model data and implement reliable persistence with PostgreSQL, SQLAlchemy or Django ORM, migrations, indexing, transactions, and query optimization.
  • Write maintainable, typed, tested Python using pytest, type hints, ruff, mypy or pyright, and clear module boundaries.
  • Build and operate asynchronous and distributed workflows with asyncio, Celery, RQ, Dramatiq, Kafka, Redis, or cloud-native queues.
  • Own production quality through logging, metrics, tracing, error handling, CI/CD, containerization, and incident response.
  • Review code, improve architecture, document decisions, and mentor engineers on Python patterns, testing, and maintainability.

Must-have skills

  • Strong production experience with Python 3.12+ and knowledge of language changes through Python 3.14, including typing, async, packaging, and runtime behavior.
  • Backend API experience with FastAPI, Django, Flask, or similar, including validation, authentication, authorization, pagination, versioning, and error design.
  • Practical database skill with PostgreSQL, schema design, migrations, transactions, indexes, query plans, and ORM tradeoffs.
  • Testing discipline with pytest, fixtures, parametrization, mocking boundaries, integration tests, contract tests, and CI enforcement.
  • Ability to write typed, maintainable Python using dataclasses, Pydantic v2, protocols, generics where useful, ruff, and mypy or pyright.
  • Concurrency and reliability knowledge covering asyncio, thread/process pools, task queues, retries, idempotency, backpressure, and failure modes.
  • Production engineering skills with Docker, Linux basics, cloud services, environment configuration, secrets handling, logging, metrics, and tracing.

Nice to have

  • Experience building data pipelines or ML-adjacent services with Pandas, Polars, PyArrow, Airflow, Dagster, or similar tools.
  • Knowledge of event-driven systems using Kafka, Redpanda, RabbitMQ, SNS/SQS, Pub/Sub, or equivalent messaging platforms.
  • Experience with OpenTelemetry, structured logging, Sentry, Prometheus, Grafana, or cloud observability tools.
  • Familiarity with free-threaded CPython efforts, Python performance profiling, C extensions, Rust extensions, or native library integration.
  • Infrastructure-as-code and deployment experience with Terraform, Kubernetes, GitHub Actions, GitLab CI, or cloud deployment pipelines.
How to interview

8 Python interview questions that reveal real depth

These are the kinds of questions our engineers use in technical interviews. Each comes with what a strong answer sounds like.

Full set: 25 Python questions by level, with red flags
  1. Q1

    Walk me through how you would design a FastAPI service that handles user-facing requests and long-running background work.

    Strong answer: A strong candidate separates request handling from job execution, validates input with Pydantic v2, persists job state, and enqueues work through Celery, RQ, Dramatiq, or a cloud queue. They discuss idempotency, retries, timeouts, cancellation, observability, and user-visible status. They avoid doing heavy work in the request path and define clear failure behavior.

  2. Q2

    How do you decide between synchronous Python, asyncio, threads, processes, and a task queue?

    Strong answer: A strong candidate ties the choice to the workload. Sync code is simpler for normal CRUD. asyncio helps with high-concurrency I/O if the libraries are async-safe. Threads can hide blocking I/O but do not solve CPU-bound work under the traditional GIL. Processes or external workers help CPU-bound jobs. Queues add durability, retries, and operational control.

  3. Q3

    What are the most important things you check when reviewing a Python pull request?

    Strong answer: A strong candidate looks beyond style. They check data model changes, transaction boundaries, error handling, test coverage, types, logging, security, backward compatibility, and performance. They notice hidden shared state, mutable defaults, broad exceptions, slow queries, blocking calls in async code, and unclear ownership. They also consider whether the design is easy to change later.

  4. Q4

    Describe how you would diagnose a slow Python API endpoint in production.

    Strong answer: A strong candidate starts with measurement, not guessing. They use traces, structured logs, metrics, and profiling to separate database time, network calls, serialization, lock contention, and Python CPU time. They inspect query plans and N+1 patterns, reproduce with realistic data, add focused benchmarks if needed, and ship the smallest safe fix with monitoring.

  5. Q5

    How do you approach type hints in a large Python codebase?

    Strong answer: A strong candidate uses typing to clarify contracts and catch change-related bugs without turning the codebase into ceremony. They mention gradual adoption, strictness by module, mypy or pyright in CI, typed boundaries, protocols for dependency inversion, and avoiding excessive generics. They understand runtime validation is separate from static typing and often use Pydantic at external boundaries.

  6. Q6

    What pitfalls have you seen with ORMs such as SQLAlchemy or Django ORM?

    Strong answer: A strong candidate discusses N+1 queries, lazy loading surprises, incorrect transaction scope, overusing ORM objects as domain models, unsafe migrations, and hidden performance costs. They know when to use eager loading, raw SQL, query plans, constraints, and explicit indexes. They treat the database as a core part of the system, not just a persistence detail.

  7. Q7

    How would you structure tests for a Python service that uses PostgreSQL, Redis, and an external payment API?

    Strong answer: A strong candidate separates unit tests from integration and contract tests. They use pytest fixtures, test containers or isolated databases for real PostgreSQL behavior, and avoid over-mocking critical persistence logic. Redis can be real or a close test substitute depending on risk. External APIs get contract tests, recorded responses where appropriate, and mocked failure modes.

  8. Q8

    What changes in recent Python versions matter for production teams in 2026?

    Strong answer: A strong candidate mentions practical effects, not release-note trivia. They understand Python 3.12 to 3.14 improvements around performance, typing, error messages, asyncio, packaging, and experimental runtime work such as free-threaded builds and JIT-related efforts. They are cautious about dependency compatibility, container base images, CI matrices, and rolling upgrades before relying on new runtime features.

Job description

Senior Python engineer job description

A ready-to-paste template. Or skip the posting entirely: send it to us as your brief and get a scored shortlist in 48 hours.

Mid and lead versions
About the role
We are hiring a Senior Python Engineer to build and operate backend systems for a remote product team. You will work on APIs, services, data workflows, and production reliability using modern Python.

What you'll do
Design and maintain Python services with FastAPI, Django, Flask, or similar tools.
Build reliable integrations with PostgreSQL, Redis, queues, and third-party APIs.
Write clear, tested, typed Python using pytest, ruff, and mypy or pyright.
Improve performance, observability, error handling, and deployment safety.
Review code, shape technical decisions, and mentor other engineers.
Collaborate with product, design, and infrastructure teammates in a remote environment.

What you'll bring
Strong experience with Python 3.12+ in production.
Good judgment around async code, background jobs, transactions, and distributed failures.
Practical database experience, especially with PostgreSQL and ORM tradeoffs.
Comfort with Docker, CI/CD, logging, metrics, and cloud services.
A habit of writing maintainable code and explaining tradeoffs clearly.
Experience owning systems after deployment, not just shipping features.
Why teams choose Octogle

What you get with Python

Pre-Vetted Expertise

Every Python developer on OctogleHire passes a rigorous vetting process covering technical skills, communication, and problem-solving ability.

Start in Days, Not Months

Skip the lengthy recruitment cycle. Our Python engineers are ready to integrate with your team and start delivering within days.

Up to 60% Cost Savings

Access world-class Python talent at a fraction of the cost of local hires, without compromising on quality or experience.

Risk-Free Trial Period

Every Python engagement starts with a trial period. If you're not completely satisfied, you pay nothing.

What you get

The engagement, as a spec sheet

Shortlist3–5 scored profiles in 48 hoursEach with a technical assessment, a system-design write-up and reference checks already completed.
EngagementFull-time on one clientIn your repo, your standups and your on-call rotation. Part-time from 20 hours on request.
RateOne published hourly rateOur margin is printed on every invoice. No placement fee and no annual minimum.
Trial14-day replacement guarantee30 days on Marketplace. If the fit is wrong we re-shortlist inside 48 hours.
NoticeTwo weeksNo long-term lock-in and no cancellation fee.
ComplianceHandled in 30+ countriesContracts, IP assignment, payroll and local employment law. You receive a single invoice.
IPYours from the first commitAssigned in the master agreement, signed before repository access is granted.
SecurityISO 27001, GDPR, CCPAEU or US data residency available on request.
Compare

How OctogleHire compares

Vetting

Agency

Resume screening only

Freelance

Self-reported skills

OctogleHire

5-stage technical vetting (1 in 25 pass rate)

Time to Hire

Agency

6–12 weeks

Freelance

Weeks of filtering

OctogleHire

48 hours to first match

Cost

Agency

$20K–$40K placement fees

Freelance

Low rates, variable quality

OctogleHire

40–60% less, no placement fee

Compliance

Agency

You manage it

Freelance

You manage it

OctogleHire

Fully managed (30+ countries)

Replacement

Agency

30–90 days (if any)

Freelance

None

OctogleHire

14–30 day replacement guarantee

Support

Agency

Account rep (9-5)

Freelance

Ticket system

OctogleHire

Dedicated account manager

Daniel bell
“We in need of a handful of developers for our internal CRM build after speaking with multiple agencies and receiving some quotations we sat down with Yaseen from Octogle and we were pleasantly surprised to see what was available for us within their talent pool. we took on three developers saving upwards of circa £6000 per month and developing the software in record time exactly how we wanted it. Highly suggest anyone to use octogle hire if you’re looking for a cost-effective high-quality software development solution.”
Daniel bellCMO, TNW Energy3Senior full stack developerss hired£225,000saved per year
Questions

Questions engineering leaders ask

Hire a Python developer when your product needs fast backend delivery, strong data workflows, automation, AI or ML integration, or a mature web framework such as Django or FastAPI. Go may fit very high-throughput infrastructure services. Java may fit large enterprise platforms. Node.js may fit full-stack JavaScript teams. Python is strongest when developer productivity, ecosystem depth, and integration speed matter.

Test production judgment, not just syntax. Ask candidates to design an API, model data, debug a slow endpoint, review flawed Python code, and explain async versus background workers. Include pytest, PostgreSQL, typing, error handling, and deployment concerns. A senior candidate should explain tradeoffs, failure modes, and maintenance impact in plain language.

It depends on codebase quality, onboarding, domain complexity, and access to decision makers. A strong senior engineer can usually start fixing contained issues quickly, but deeper productivity requires understanding data models, deployment paths, incident history, and product rules. Good onboarding includes local setup, architecture notes, test data, runbooks, and a first task that exercises the full delivery path.

Use a freelance Python developer for a defined project, migration, integration, audit, or short-term capacity gap. Hire full-time when the engineer must own architecture, production reliability, roadmap tradeoffs, and ongoing product knowledge. Python systems often accumulate domain logic in services and data models, so long-term ownership matters when the work is core to the business.

Yes, if the team works with clear tickets, written decisions, healthy CI, observable environments, and regular technical communication. Remote Python engineers need access to logs, traces, local setup instructions, test fixtures, and deployment documentation. The biggest risk is not distance; it is undocumented context and slow feedback from product, security, or infrastructure stakeholders.

For web backends, FastAPI and Django are the most common signals to evaluate, with Flask still present in many services. Strong candidates understand framework tradeoffs rather than only one tool. They should know validation, dependency injection or service layers, middleware, authentication, testing, and deployment. For data and workflow systems, look for Airflow, Dagster, Celery, RQ, or similar experience.

Common mistakes include overvaluing algorithm puzzles, ignoring database skill, and treating Python as easy enough for anyone to write well. Poor Python systems often fail through weak boundaries, slow queries, unsafe migrations, blocking async code, missing tests, and unclear ownership. Evaluate candidates on maintainability, production debugging, and their ability to make simple designs that survive change.

Use a small realistic task: an API endpoint, background job, or data import with tests. Look for readable structure, explicit errors, type hints where helpful, good pytest coverage, safe database handling, and simple dependency management. Avoid oversized assignments. A follow-up discussion is essential because strong engineers can explain shortcuts, production changes, and tradeoffs clearly.

You'll receive 3–5 vetted candidate profiles within 48 hours of your demo call. Most companies go from first intro to signed contract in under 5 business days — compared to 6–12 weeks with traditional agencies.

Every developer passes a 5-stage process: application screening, stack-specific technical assessment, live system design interview, soft-skills evaluation, and reference checks. From over 25,000 applicants reviewed, only 1,000 have been accepted into our network.

OctogleHire engineers start at £15/hr (about $19), with senior engineers at about £24/hr. That is roughly 50–65% less than the loaded cost of an equivalent in-house hire in the UK, US or Australia — a senior UK hire costs about £48/hr once employer costs are included. There are no upfront fees or placement commissions; you pay one published hourly rate once your engineer starts.

Every placement includes a risk-free replacement guarantee — 14 days on our On-Demand plan and 30 days on our Marketplace plan. If a developer doesn't meet your expectations, we'll find a replacement at no additional cost and manage the transition for you. Our replacement rate is under 6%.

No sales call in between

Send the brief. Meet Python engineers on Thursday.

Twenty minutes with an Octogle engineer, then three to five scored profiles inside 48 hours. Free to post, with a replacement guarantee on every placement.