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Senior Fastapi Developer Jobs in Virginia (NOW HIRING)

NT Concepts

Python Developer

Herndon, VA · On-site +1

$51.75 - $71.25/hr

This position requires mid to senior level of experience, a passion for mission support, and a ... Experience designing and implementing RESTful APIs using Python frameworks (FastAPI, Flask, Django)

WorkNova LLC

Python Developer

Reston, VA · On-site

$52.25 - $72/hr

Position Summary The Senior Python Developer will design, develop, test, and implement cloud native ... or FastAPI • Knowledge of authentication and authorization mechanisms (JWT, OAuth2) • ...

IntelliTech

Senior DevSecOps Engineer

Alexandria, VA · On-site

$111.40K - $152.80K/yr

The application is a supply chain simulation platform built on Python, FastAPI, React, and MongoDB ... Active DoD Secret clearance. * 8+ years of professional experience in DevOps, platform engineering ...

IntelliTech LLC

Senior DevSecOps Engineer

Alexandria, VA · On-site

$111.40K - $152.80K/yr

The application is a supply chain simulation platform built on Python, FastAPI, React, and MongoDB ... Active DoD Secret clearance. * 8+ years of professional experience in DevOps, platform engineering ...

Seekr

Senior AI Solutions Engineer

Reston, VA · On-site

$57.50 - $74/hr

Capable of developing prototype solutions using common tools (e.g., FastAPI, React) * Familiar with generative AI concepts like RAG, prompt engineering, agents, structured output, multi-modal LLMs ...

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Senior Fastapi Developer information

What are the key skills and qualifications needed to thrive as a Senior FastAPI Developer, and why are they important?

To thrive as a Senior FastAPI Developer, you need deep expertise in Python, RESTful API design, and experience building scalable web backends, typically supported by a degree in computer science or related field. Familiarity with FastAPI, Docker, cloud platforms (such as AWS or Azure), and CI/CD tools is highly valued, along with proficiency in testing frameworks. Strong problem-solving, leadership, and communication skills help you collaborate effectively with cross-functional teams and mentor junior developers. These skills enable the delivery of robust, efficient, and maintainable APIs that support business goals and high user demands.

What are some common challenges faced by Senior FastAPI Developers when scaling applications, and how can these be addressed?

Senior FastAPI Developers often encounter challenges related to managing high concurrency, optimizing API performance, and ensuring robust security as applications scale. To address these, it’s important to implement asynchronous programming practices, leverage efficient database queries, and utilize API gateways for better traffic management. Collaboration with DevOps and QA teams is also essential to automate deployments and monitor system health, ensuring smooth scaling and reliable user experiences.

What does a Senior FastAPI Developer do?

A Senior FastAPI Developer designs, develops, and maintains backend web applications using the FastAPI framework in Python. They are responsible for building scalable APIs, optimizing performance, ensuring security best practices, and integrating with databases and external services. Senior developers also mentor junior team members, contribute to architecture decisions, and collaborate closely with front-end engineers and stakeholders to deliver robust software solutions.
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Senior Fastapi Developer jobs near you

Senior AI Software Engineer (Generative AI / AWS Bedrock)

WorkNovas LLC

Reston, VA • On-site

$127.40K - $168K/yr

Contractor

Posted 8 days ago

Job description

F2F interviewSenior AI Software Engineer (Generative AI / AWS Bedrock)

Reston, VA, 3 days onsite

Description:

• 6+ years software engineering experience

• 3+ years building AI/ML-powered applications

• Experience deploying AI systems into production

Python Programming is must 

About the Role

We are seeking a Senior AI Software Engineer to design and build production-grade AI applications powered by large language models and foundation models. In this role, you will develop scalable commercial solutions using AWS Bedrock and other AI model providers, integrating advanced AI capabilities into real-world products and platforms.

You will work at the intersection of AI engineering, cloud architecture, and product development, building intelligent systems that leverage multiple foundation models for reasoning, automation, and data-driven insights.

This is a hands-on role for engineers passionate about transforming cutting-edge AI capabilities into robust, scalable commercial applications.

What You’ll Do

Technology Stack and AI/LLM Programming Expertise

• Hands-on experience with LLM APIs or foundation models

• Experience building:

o RAG systems

o AI copilots

o conversational agents

o automated workflows

o AI-driven analytics

o document AI solutions

• Python

• Java / TypeScript / Go (any backend language)

• Design and develop production AI applications using models available via AWS Bedrock and external providers

o AWS Bedrock

§ Anthropic Claude

§ Amazon Titan

§ Meta Llama

§ Cohere

§ OpenAI

o OpenAI

o Open-source LLMs

o S3, API Gateway, Step Functions, Lambda / ECS / EKS, Docker / Kubernetes

o FastAPI

o Terraform

Create pipelines for:

o embeddings

o document ingestion

o knowledge indexing

o model evaluation

• Vector databases (pg-vector, S3-vector, OpenSearch, FAISS)

• Embeddings and semantic search

• Prompt engineering

• Tracing, hallucination detection, cost monitoring, prompt performance, drift detection

• Model evaluation frameworks

• Experience with LangChain, LangGraph, LlamaIndex, or AI orchestration frameworks

• LLM Monitoring and Observability

• Experience with multi-model routing systems

• Experience building AI agents or tool-using LLMs

• Knowledge of AI safety, guardrails, and prompt management

• Experience deploying models with Docker and Kubernetes

• MCP, FastMCP

• Reinforcement Learning

• AWS SageMaker with MLOPs

• Experience with Bedrock API [Like from Lambda or Other services]

• Design high-performance AI APIs and microservices

• Optimize latency, reliability, and cost of model inference

• Implement evaluation pipelines and monitoring for AI systems

What We’re Looking For

The ideal candidate:

• Thinks like a systems architect and builder

• Has shipped real AI products to production

• Understands tradeoffs between models

• Can design robust AI pipelines

• Is comfortable working with rapidly evolving AI technologies

Example Problems You’ll Work On

• Build an enterprise knowledge assistant using Bedrock

• Create AI agents that automate complex workflows

• Develop document intelligence pipelines for financial or operational data

• Design multi-model orchestration frameworks

• Optimize LLM cost, latency, and reliability