Writing a job description from scratch is where most hiring timelines quietly lose their first week. These four templates cover the roles hiring managers ask us about most often — AI Developer, React Developer, Data Engineer, and Data Scientist — so you can copy, fill in the bracketed placeholders, and post within the hour instead of starting from a blank page.
Each template follows the same structure: role overview, key responsibilities, required qualifications, nice-to-have skills, and what to offer — the sections candidates actually read, in the order they expect to read them.
Jump to a template: AI Developer · React Developer · Data Engineer · Data Scientist
# Template 1 — AI Developer
Job Title: AI Developer
About the Role
[Your Company Name] is looking for an AI Developer to design, build, and deploy machine learning and generative AI systems that solve real business problems. You'll work across the model lifecycle — from data preparation through production deployment — collaborating closely with product and engineering to ship AI features that actually get used, not just demoed.
Key Responsibilities
- •Design, train, and evaluate machine learning or generative AI models for [specific use case, e.g. fraud detection, recommendation, document processing].
- •Build and maintain data pipelines and feature stores that keep models fed with clean, current data.
- •Deploy models to production and monitor performance, drift, and reliability over time.
- •Collaborate with product managers and engineers to translate business requirements into model requirements.
- •Evaluate and integrate third-party AI/LLM APIs where building in-house isn't the right call.
- •Document model decisions, limitations, and evaluation metrics for technical and non-technical stakeholders.
Required Qualifications
- •[X]+ years of experience building and deploying machine learning or AI systems in production, not only research or notebook work.
- •Strong proficiency in Python and common ML/DL frameworks (PyTorch, TensorFlow, or Scikit-learn).
- •Experience with at least one cloud platform (AWS, Azure, or GCP) for model training and deployment.
- •Solid understanding of model evaluation, including precision/recall tradeoffs and how to communicate them to non-technical stakeholders.
- •Experience working with structured and unstructured data at [expected scale].
Nice to Have
- •Experience with LLM/GenAI tooling (LangChain, LlamaIndex, RAG pipelines, or fine-tuning).
- •MLOps experience (MLflow, Kubernetes, CI/CD for ML).
- •Domain experience in [your industry, e.g. fintech, healthcare, e-commerce].
What We Offer
- •[Compensation range or 'Competitive compensation based on experience']
- •[Remote / hybrid / on-site — specify]
- •[Benefits, equity, or other perks specific to your company]
How to Apply
[Application instructions — link, email, or ATS reference]
# Template 2 — React Developer
Job Title: React Developer
About the Role
[Your Company Name] is looking for a React Developer to build fast, reliable, user-facing interfaces for [your product]. You'll own frontend features end-to-end — from component architecture through performance and accessibility — working closely with design and backend engineering to ship a product people actually enjoy using.
Key Responsibilities
- •Build and maintain React components and features for [your product/platform].
- •Translate design mockups into responsive, accessible, production-quality UI.
- •Integrate frontend features with backend APIs and manage application state.
- •Optimize for performance — load time, rendering efficiency, and bundle size.
- •Write unit and integration tests for frontend code.
- •Participate in code review and contribute to frontend architecture decisions.
Required Qualifications
- •[X]+ years of professional experience building production React applications.
- •Strong proficiency in JavaScript/TypeScript, React, and modern frontend tooling.
- •Experience with state management (Redux, Context API, or equivalent) in real applications.
- •Comfortable working with REST or GraphQL APIs.
- •Understanding of responsive design, cross-browser compatibility, and basic accessibility (WCAG) principles.
Nice to Have
- •Experience with Next.js or server-side rendering.
- •Node.js experience for full-stack contributions.
- •Experience building in a regulated or compliance-sensitive industry (healthcare, fintech).
What We Offer
- •[Compensation range or 'Competitive compensation based on experience']
- •[Remote / hybrid / on-site — specify]
- •[Benefits, equity, or other perks specific to your company]
How to Apply
[Application instructions — link, email, or ATS reference]
# Template 3 — Data Engineer
Job Title: Data Engineer
About the Role
[Your Company Name] is looking for a Data Engineer to design and maintain the data infrastructure that powers analytics, reporting, and (where relevant) machine learning across our business. You'll build reliable pipelines that keep data accurate, fresh, and accessible to the teams that depend on it.
Key Responsibilities
- •Design, build, and maintain ETL/ELT pipelines that move and transform data from [your key sources, e.g. product database, third-party APIs, event streams].
- •Build and maintain the data warehouse layer that feeds analytics and BI dashboards.
- •Ensure data quality, consistency, and freshness across pipelines, with monitoring and alerting for failures.
- •Optimize pipeline performance and cost as data volume grows.
- •Collaborate with analytics, data science, and product teams to understand data needs and translate them into pipeline design.
- •Document data models, pipeline architecture, and data lineage.
Required Qualifications
- •[X]+ years of experience building production data pipelines at [expected scale].
- •Strong SQL skills and proficiency in Python or Scala.
- •Experience with orchestration tools (Airflow, dbt, or equivalent).
- •Experience with a cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks).
- •Understanding of data modeling principles for analytics and reporting use cases.
Nice to Have
- •Experience with streaming data (Kafka, Kinesis, or similar).
- •Experience supporting machine learning feature pipelines.
- •Experience with [your specific platform, e.g. Shopify, Salesforce, HL7/FHIR] data integrations.
What We Offer
- •[Compensation range or 'Competitive compensation based on experience']
- •[Remote / hybrid / on-site — specify]
- •[Benefits, equity, or other perks specific to your company]
How to Apply
[Application instructions — link, email, or ATS reference]
# Template 4 — Data Scientist
Job Title: Data Scientist
About the Role
[Your Company Name] is looking for a Data Scientist to turn our data into decisions. You'll design experiments, build predictive models, and work directly with stakeholders to answer questions that shape product and business strategy — with an emphasis on findings that are actually actionable, not just interesting.
Key Responsibilities
- •Analyze [your key business data, e.g. user behavior, transactions, operational metrics] to answer specific business questions.
- •Design and run experiments (A/B tests or similar) and interpret results rigorously.
- •Build predictive or statistical models to support [your use case, e.g. churn prediction, demand forecasting, pricing].
- •Partner with product, marketing, or operations stakeholders to define what to measure and why.
- •Communicate findings clearly to non-technical stakeholders, with a recommendation, not just a chart.
- •Collaborate with data engineering to ensure the data needed for analysis is reliable and accessible.
Required Qualifications
- •[X]+ years of experience in a data science or applied statistics role.
- •Strong SQL and Python (pandas, scikit-learn, or equivalent) skills.
- •Solid grounding in statistics — hypothesis testing, experiment design, and common pitfalls in interpreting results.
- •Experience translating ambiguous business questions into a measurable analysis plan.
- •Experience presenting findings to non-technical audiences.
Nice to Have
- •Experience with a BI tool (Looker, Tableau, or Power BI) for self-serve stakeholder reporting.
- •Experience with causal inference or more advanced experimentation design.
- •Domain experience in [your industry, e.g. e-commerce, fintech, healthcare].
What We Offer
- •[Compensation range or 'Competitive compensation based on experience']
- •[Remote / hybrid / on-site — specify]
- •[Benefits, equity, or other perks specific to your company]
How to Apply
[Application instructions — link, email, or ATS reference]
# How to Use These Templates
Fill in Every Bracketed Placeholder
Especially [X]+ years and the compensation/location fields. A JD with unfilled brackets is the fastest way to signal a rushed posting to strong candidates.
Cut, Don't Just Add
If a responsibility or requirement doesn't apply to your actual role, remove it rather than leaving it in 'just in case.' Long, generic JDs get fewer qualified applicants, not more.
Keep 'Required' Short and Real
4–5 genuinely required qualifications outperforms a 12-item wishlist that screens out otherwise strong candidates who are missing one line.
Match the Tone to Your Company
These templates are intentionally neutral; adjust the voice to match how your team actually talks to candidates elsewhere (careers page, outreach emails).
# Skip the Job Posting Entirely
If writing and posting a JD, then screening the applicants who respond, isn't how you want to spend the next few weeks — CompanyBench pre-vets developers against templates like these before you ever see a profile. Most engagements start within 24-48 hours.
| Role | Hire Directly Instead |
|---|---|
| AI Developer | [Hire AI Developers →](/hire-talent/hire-ai-developers) |
| React Developer | [Hire React Developers →](/hire-talent/hire-react-js-developers) |
| Data Engineer | [Hire Data Engineers →](/hire-talent/hire-data-engineer) |
| Data Scientist | [Hire Data Scientists →](/hire-talent/hire-data-scientists) |
"For real 2026 hourly-rate benchmarks to pair with these templates, see AI Developer Cost in 2026 and React Developer Cost in 2026. Comparing hiring models before you post the role? Read Bench Hiring vs. Outsourcing.
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