$116K - $139K/yr
Programming & Data Engineering: o Strong programming proficiency in Python is a must, including ... FastAPI, Seaborn, LangChain, and LlamaIndex. o Proficiency in integrating generative AI with ...
New
$116K - $139K/yr
Programming & Data Engineering: o Strong programming proficiency in Python is a must, including ... FastAPI, Seaborn, LangChain, and LlamaIndex. o Proficiency in integrating generative AI with ...
New
$13.47 - $20.23
1% of jobs
$20.23 - $27
0% of jobs
$27 - $33.76
2% of jobs
$33.76 - $40.53
5% of jobs
$40.53 - $47.30
11% of jobs
$49.29 is the 25th percentile. Wages below this are outliers.
$47.30 - $54.06
18% of jobs
The median wage is $57.59 / hr.
$54.06 - $60.83
24% of jobs
$66 is the 75th percentile. Wages above this are outliers.
$60.83 - $67.60
18% of jobs
$67.60 - $74.36
13% of jobs
$74.36 - $81.13
5% of jobs
$81.13 - $87.90
3% of jobs
$13
$59
$87
A Python FastAPI Developer is responsible for designing, developing, and maintaining backend applications using FastAPI, a modern web framework for building APIs with Python. They work on creating high-performance APIs, integrating with databases, implementing authentication, and ensuring scalability. This role often involves working with asynchronous programming, cloud services, and containerization tools like Docker. Developers collaborate with teams to create efficient, secure, and well-documented API endpoints for web and mobile applications.
To thrive as a Python FastAPI Developer, you need strong proficiency in Python programming, experience designing RESTful APIs with FastAPI, and a background in web development concepts. Familiarity with version control systems like Git, containerization tools such as Docker, and knowledge of cloud platforms or SQL/NoSQL databases are commonly required, and certifications in cloud services or Python development can be advantageous. Excellent problem-solving skills, effective communication, and the ability to collaborate in agile teams help developers contribute efficiently to complex projects. These competencies ensure robust, scalable backend solutions and smooth coordination within development teams to meet business goals.
A Python FastAPI Developer typically spends their day designing, developing, and maintaining RESTful APIs to support web or mobile applications. This involves writing clean and efficient Python code, collaborating with frontend developers or other backend engineers to integrate new features, and ensuring the application meets performance and security standards. Developers also participate in code reviews, debugging, and continuous integration processes, while regularly communicating with product managers or stakeholders to align on project requirements. Staying up to date with FastAPI enhancements and industry best practices is also a common part of the role.
$116K - $139K/yr
Other
Posted yesterday
JD
8-10 years of relevant experience in Apps Development or systems analysis role
Core AI/ML Foundations:
o Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
·Generative AI & LLM Expertise:
o Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
o Critical: Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
o Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc.
o Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates.
o Hands-on experience with agentic framework-based use case implementation.
o Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features.
Programming & Data Engineering:
o Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex.
o Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools.
o Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval.
o Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing.
· Deployment & MLOps:
o Critical: Hands-on experience deploying GenAI-based models to production environments.
o Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines.
o Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
· Cloud & Containerization:
o Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment.
· Soft Skills:
o Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems