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Junior Fastapi Developer Jobs in Ashburn, VA (NOW HIRING)

Mentor junior engineers and contribute to Steampunk's AI engineering best practices, tooling, and ... Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and ...

Senior LLMOps Engineer

Mclean, VA · On-site

$145K - $185K/yr

Mentor junior engineers and contribute to Steampunk's AI engineering best practices, tooling, and ... Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and ...

Senior LLMOps Engineer

Mclean, VA · On-site

$145K - $185K/yr

Mentor junior engineers and contribute to Steampunk's AI engineering best practices, tooling, and ... Proficiency in Python and operational tooling such as FastAPI, PyTorch, LangChain, LlamaIndex, and ...

Work closely with senior ML engineers, software developers, and government customers; mentor junior ... Deploying LLM APIs (FastAPI,gRPC) at scale, handlinglatencyand load balancing. * Building multitool ...

You will serve as a technical anchor for the team-mentoring junior engineers, setting engineering ... FastAPI, asyncio) and distributed service architectures. Production Experience at Scale A track ...

Showing results 21-40

Junior Fastapi Developer information

See Ashburn, VA salary details

$24.5K

$91K

$140.6K

How much do junior fastapi developer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for junior fastapi developer in Ashburn, VA is $90,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,500.00 and $89,000.00 per year, depending on experience, location, and employer.

What is a Junior FastAPI Developer?

Junior FastAPI Developers are entry-level software engineers who specialize in building web applications and APIs using FastAPI, a modern Python web framework. They are responsible for writing, testing, and maintaining backend code, often under the guidance of more experienced developers. Their tasks typically include developing RESTful APIs, integrating databases, and ensuring application performance and security. Junior FastAPI Developers usually have a basic understanding of Python, web technologies, and REST principles. They play an important role in supporting projects, learning best practices, and growing their technical skills.

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

To thrive as a Junior FastAPI Developer, you need foundational knowledge of Python programming, RESTful API concepts, and experience working with FastAPI frameworks, supported by a relevant degree or coding bootcamp. Familiarity with Git for version control, SQL or NoSQL databases, and containerization tools like Docker is typically expected. Strong problem-solving skills, eagerness to learn, and effective communication make candidates stand out in collaborative development environments. These competencies ensure efficient, high-quality API development and seamless teamwork in agile software projects.

What are some typical challenges a Junior FastAPI Developer may face when joining a new team?

As a Junior FastAPI Developer, you may encounter challenges such as adapting to established codebases, understanding the team's API design patterns, and ensuring your code aligns with both FastAPI best practices and your organization's standards. Collaborating closely with senior developers and participating in code reviews can help accelerate your learning process. Additionally, you may need to quickly familiarize yourself with related tools such as Docker, Git, and testing frameworks, as well as the team's workflow for deploying and maintaining APIs in production environments.

What is the difference between Junior Fastapi Developer vs Junior Python Developer?

AspectJunior Fastapi DeveloperJunior Python Developer
Required CredentialsBasic Python knowledge, familiarity with FastapiBasic Python knowledge, possibly some frameworks
Work EnvironmentWeb backend development, API creationGeneral software development, scripting
Employer & Industry UsageTech companies, startups, web servicesBroad industry, including data analysis, automation
Common Search & ComparisonYesYes

The main difference is that a Junior Fastapi Developer specializes in building APIs using Fastapi, while a Junior Python Developer has broader Python programming skills without specific focus on web APIs. Fastapi developers typically work in web backend environments, whereas Python developers may work across various domains.

What are the most commonly searched types of Fastapi Developer jobs in Ashburn, VA?

The most popular types of Fastapi Developer jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Junior Fastapi Developer jobs?

Cities near Ashburn, VA with the most Junior Fastapi Developer job openings:

Full-time

Re-posted 2 days ago


Job description

Job Summary:
The Software Engineering Institute at Carnegie Mellon University is seeking an AI Engineer to conduct research in applied artificial intelligence and develop robust AI solutions for the defense and national security sectors. The role involves designing and deploying AI models and collaborating with interdisciplinary teams to operationalize AI technologies for mission capabilities.
Responsibilities:
• Design, develop, and fine‑tune a variety of AI models.
• Design autonomous agents and multi‑step pipelines using LangChain, ReAct, tool‑calling, or custom orchestration; employ the Model Context protocol to manage stateful interactions.
• Build Retrieval‑Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications.
• Implement end‑to‑end data pipelines, ETL processes, and back‑end services (Python, C/C++, Java) that feed data to models.
• Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning; maintain model registries, monitoring, and version control of context protocols.
• Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments.
• Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation.
• Stay current with emerging LLM architectures, agentic paradigms, PEFT/LoRA methods, and AI‑safety techniques; translate new research into operational capabilities.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field with at least eight (8) years of relevant experience, or a MS degree in the same with at least five (5) years of relevant experience.
• You will be subject to a background investigation and must be able to obtain and maintain an active Department of War (DoW) security clearance.
• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.
• Proficiency in Python and at least one compiled language (C/C++ or Java); experience with REST/GraphQL APIs and containerization.
• Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics.
• Hands‑on experience fine‑tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools.
• Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers).
• Experience applying PEFT/LoRA methods (e.g., LoRA, adapters) to large models.
• Understanding of Model Context protocols for managing model state across multi‑turn interactions.
• Experience building evaluation frameworks, benchmarks, or data quality pipelines.
• Experience with TensorFlow, PyTorch, or JAX; knowledge of data‑pipeline tools (Airflow, Prefect, Ray) is a plus.
• Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model‑registry concepts) is desirable.
Preferred:
• Deploying LLM APIs (FastAPI, gRPC) at scale, handling latency and load balancing.
• Building multi‑tool agents, planner‑executor loops, or tool‑calling pipelines for complex decision‑making.
• Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research.
• Utilizing GPU/TPU resources, mixed‑precision training, and distributed training frameworks such as DeepSpeed or ZeRO.
• Prior work on defense, intelligence, or government‑focused AI projects and familiarity with DoW acquisition or compliance processes.
• Contributing to open‑source AI and ML libraries, agentic frameworks, or context‑protocol implementations.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.