You need a senior Python engineer who can read your Django or FastAPI codebase and ship in the first week, not a stack of resumes to sort through. Kiyansh Group places vetted contract, contract-to-hire, and direct Python, Django, FastAPI, and data professionals — senior, US-based, no offshore hand-off. Every candidate we send has been screened by someone who can actually read their code.
Tell us what you need →We staff Python roles across three engagement models: contract for defined project work or surge capacity, contract-to-hire when you want to work with someone before converting them to a full-time employee, and direct placement when you already know you want them permanently. The same vetting bar applies to all three — we don't lower the standard because an engagement is short.
Our Python bench covers backend and API work (Django, Django REST Framework, FastAPI, Flask), data engineering (pandas, PySpark, Airflow, dbt, SQL-heavy pipelines), and the ML/data-science adjacent roles that increasingly want production Python rather than notebook code. Candidates are US-based and available on your time zone. There is no offshore team behind the person you interview — the engineer you talk to is the engineer who does the work.
This is one of the strongest-demand skills we track. Kiyansh maintains live tracking of 559 open US contract IT roles across 420 companies; Python-family roles account for 52 of those 559, putting it among the most in-demand skills in the market right now. We tell you that so you calibrate expectations: strong Python contractors move fast, and the ones worth hiring are usually already interviewing elsewhere.
Vetting starts with a working-session screen, not a keyword match. A senior engineer walks the candidate through their actual recent work — a service they built, a data pipeline they own — and pushes on the decisions: why an ORM query versus raw SQL, how they handled N+1 problems in Django, where they put business logic, how they structured FastAPI dependencies and Pydantic models. People who copied a resume from a template fall apart in the first ten minutes; people who did the work explain it easily.
We check the fundamentals that separate senior from mid-level: understanding of Python's concurrency model (async/await, GIL implications, when threads help and when they don't), correct use of type hints and mypy, test discipline with pytest, and the ability to reason about database performance and migrations rather than treating the ORM as magic. For data roles we probe data modeling, idempotent pipeline design, and how they handle backfills and schema drift.
We verify identity and work authorization, confirm the person on the intro call is the person who screened, and reference-check recent engagements. We do not forward candidates we haven't spoken to. If a candidate isn't right for your role, we say so rather than padding the shortlist — a short list of real fits saves you more time than a long list of maybes.
For web and API roles, the load-bearing skills are Django and the Django REST Framework, FastAPI with Pydantic, Celery or similar for async task queues, and real SQL competence on PostgreSQL — most Python performance problems are database problems. For deployment fluency we look for Docker, CI pipelines, and comfort with at least one cloud (AWS is most common in our contract pool, followed by Azure and GCP).
For data engineering, the stack that shows up most is pandas and PySpark, Airflow or Dagster for orchestration, dbt for transformation, and warehouse experience on Snowflake, BigQuery, or Redshift. Certifications are secondary to demonstrated work — an AWS Solutions Architect or a Databricks cert is a useful signal for a data-platform role, but we weight a candidate's actual pipelines and code far more heavily than any badge.
We match to your specific stack rather than sending generalists. If your codebase is Django on PostgreSQL with Celery, we send people who have run that combination in production, not people who have 'Python' on a resume. Tell us the framework, the database, the cloud, and the domain, and we filter to genuine matches.
Because we screen from a maintained bench rather than starting a search from zero, most contract Python roles get a qualified shortlist within a few business days, and a filled seat generally lands inside one to two weeks depending on how tightly your requirements are scoped and how fast your interview loop moves. Narrow, senior, or security-cleared requirements take longer — we'd rather quote you honestly than promise a next-day miracle and send filler.
Contract engagements are typically structured as W-2 or 1099/corp-to-corp depending on the candidate and your preference, with clear rates quoted up front and no hidden markup games. Contract-to-hire includes a defined conversion path so there are no surprises if you decide to bring someone on permanently. We also act as a sub-vendor to MSPs and prime vendors on private-sector and government engagements when you need bench capacity under an existing contract.
US-based. The engineer you interview is the engineer who does the work — there is no offshore team behind them and no hand-off. We staff senior contractors on your time zone, including H-1B contractors where appropriate, all with verified work authorization.
Most standard contract Python, Django, or FastAPI roles get a qualified shortlist within a few business days and a filled seat inside one to two weeks, depending on scope and your interview speed. Highly specialized or cleared roles take longer, and we'll tell you that up front rather than pad the shortlist.
A senior engineer runs a working-session screen on the candidate's real recent work, probing Django/FastAPI architecture decisions, database performance, Python concurrency, and test discipline — not a keyword match. We verify identity and authorization, confirm the intro-call person is the person who screened, and reference-check recent engagements before forwarding anyone.
Tell Kiyansh Group your stack, seniority, and start date, and we'll send a short list of vetted Python engineers who fit — not a resume dump.
Start a conversation →