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Fastapi Developer Jobs in Brockton, MA (NOW HIRING)

The Hollister Group

AI Developer

Boston, MA · On-site

$70 - $110/hr

Develop and maintain Python-based AI applications and APIs using frameworks like FastAPI, Flask, or ... Collaborate with data engineering teams to ensure smooth ingestion, transformation, and storage of ...

Lila Sciences

Senior Software Engineer, App

Cambridge, MA

$133K - $176K/yr

Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade ... Experience with and web services for CRUD services (SQLModel, FastAPI, Django). * Orchestration ...

jobr.pro

Senior Software Engineer, App

Cambridge, MA · On-site

$144 - $240/hr

Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade ... Experience with and web services for CRUD services (SQLModel, FastAPI, Django). * Orchestration ...

New

Lila Sciences

Senior Software Engineer, App

Cambridge, MA · On-site

$133K - $176K/yr

Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade ... Experience with and web services for CRUD services (SQLModel, FastAPI, Django). * Orchestration ...

Paperless Parts

Senior Software Engineer

Boston, MA

$142K - $192K/yr

We work across a modern stack - Python (Django and FastAPI), TypeScript and React, PostgreSQL, and ... Champion Engineering Excellence: Advance our practices - testing, observability, code review, and ...

Paperless Parts

Senior Software Engineer

Boston, MA · On-site

$133K - $175K/yr

We work across a modern stack - Python (Django and FastAPI), TypeScript and React, PostgreSQL, and ... Champion Engineering Excellence: Advance our practices - testing, observability, code review, and ...

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Fastapi Developer information

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$53

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How much do fastapi developer jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for fastapi developer in Brockton, MA is $53.07, according to ZipRecruiter salary data. Most workers in this role earn between $40.58 and $64.95 per hour, depending on experience, location, and employer.

What are some common challenges FastAPI developers face when integrating third-party services or APIs?

FastAPI Developers often encounter challenges when integrating third-party services, such as handling authentication protocols (like OAuth2), ensuring compatibility between JSON schemas, and managing asynchronous calls to avoid performance bottlenecks. It’s also common to troubleshoot and adapt to inconsistencies in external API documentation or rate limits. Collaborating closely with frontend teams and DevOps professionals helps streamline these integrations, ensuring robust, scalable API solutions.

What is the difference between Fastapi Developer vs Backend Developer?

AspectFastapi DeveloperBackend Developer
Required SkillsPython, Fastapi, REST APIs, async programmingMultiple languages (Python, Java, Node.js), REST/SOAP APIs, databases
Work EnvironmentWeb development, API-focused projects, microservicesBroader software development, server-side logic, database management
Industry UsageTech startups, SaaS, API-driven servicesEnterprise, e-commerce, finance, various industries

Fastapi Developers specialize in building high-performance APIs using Python and Fastapi, often within microservices architectures. Backend Developers have a broader scope, working with multiple languages and technologies to develop server-side applications across various industries. While Fastapi Developers focus on API efficiency, Backend Developers handle comprehensive backend systems.

What are the key skills and qualifications needed to thrive as a FastAPI developer?

To thrive as a FastAPI Developer, you need strong proficiency in Python programming, RESTful API design, and experience with FastAPI, often supported by a background in computer science or related fields. Familiarity with tools like SQL/NoSQL databases, Docker, and cloud platforms, as well as knowledge of asynchronous programming and API documentation tools like Swagger, is typically required. Excellent problem-solving skills, attention to detail, and effective communication set outstanding FastAPI developers apart. These skills are crucial for building reliable, high-performance APIs that meet modern application demands and facilitate seamless team collaboration.

What is a FastAPI developer?

A FastAPI Developer is a software engineer who specializes in building web applications and APIs using the FastAPI framework, which is a modern, fast (high-performance) web framework for Python. FastAPI Developers are responsible for designing, developing, and maintaining backend services and APIs that are efficient, robust, and scalable. They often work with databases, authentication, and deployment processes, and ensure that the API endpoints adhere to best practices for security and performance. Their work is crucial for enabling smooth communication between front-end applications and backend systems.
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Fastapi Developer jobs near you

Senior Software Engineer, Data

Lila Sciences

Cambridge, MA

$133K - $176K/yr

Full-time

Re-posted 13 days ago

Job description

Your Impact at LILA

Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Data Platform Team (Data), where you'll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

About The Team

The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

  • Design & Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.
  • Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
  • Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
  • Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
  • Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 5-8+ years of engineering experience building and deploying large-scale backend systems in production.
  • Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
  • Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).
  • Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
  • Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
  • Hands on experience using AI coding assistants to drive productivity is required.
  • Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
  • Problem Solving: Proven ability to deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

  • Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
  • Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
  • Experience with laboratory devices, robotics, or hardware

Apply