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Senior Python Ai Jobs in Washington, DC (NOW HIRING)

Sr. Python Developer

Rockville, MD

$123.80K - $166.70K/yr

Position: Sr. Python Developer Location: Rockville, MD / Tysons, VA #HYBRID Duration: 12 months ... Familiarity with front-end technologies such as Angular and Node.js * AI/ML Capabilities * 2+ years ...

Python Developer

Reston, VA

$52.25 - $72/hr

We are seeking a Senior Python Developer to support the design, development, and scaling of cloud ... AI-driven capabilities into applications. Skills: Strong proficiency in Python and backend ...

318 - Senior Python Developer

Fort George G Meade, MD

$134.70K - $181.30K/yr

ARSIEM is looking for a motivated Senior Python Developer with the right knowledge, skills, and ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Python Developer

Reston, VA · On-site

$52.25 - $72/hr

Position Summary The Senior Python Developer will design, develop, test, and implement cloud native ... AI assisted development tools • Use AI tools responsibly to: o Accelerate development while ...

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Showing results 1-20

Senior Python Ai information

See Washington, DC salary details

$62.3K

$160.8K

$220.9K

How much do senior python ai jobs pay per year?

As of May 29, 2026, the average yearly pay for senior python ai in Washington, DC is $160,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,600.00 and $185,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Python AI Engineer, and why are they important?

To thrive as a Senior Python AI Engineer, you need deep expertise in Python programming, machine learning algorithms, and a strong foundation in mathematics and data science, often supported by a relevant degree. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP), and experience deploying AI models in production are typically required. Exceptional problem-solving, communication, and project leadership skills set outstanding candidates apart. These capabilities enable the development of robust, scalable AI solutions that drive business value and innovation.

What are some common challenges faced by Senior Python AI engineers when integrating AI models into production systems?

Senior Python AI engineers often encounter challenges such as ensuring the scalability and reliability of AI models in production environments. This includes managing dependencies, handling real-time data processing, and monitoring model performance to prevent issues like data drift. Collaboration with DevOps and data engineering teams is essential to streamline deployment pipelines and maintain system robustness. Additionally, keeping up with evolving AI frameworks and best practices is crucial for long-term project success.

What does a Senior Python AI Engineer do?

A Senior Python AI Engineer is responsible for designing, developing, and deploying artificial intelligence solutions using the Python programming language. They work on building machine learning models, data pipelines, and integrating AI systems into applications. These professionals also lead teams, mentor junior engineers, and ensure the scalability and efficiency of AI projects. Their expertise is crucial for translating business needs into technical solutions that leverage the latest advancements in AI.

What is the difference between Senior Python Ai vs Data Scientist?

AspectSenior Python AiData Scientist
Required CredentialsBachelor's or higher in CS, AI, or related; experience with Python, AI frameworksBachelor's or higher in CS, Statistics, or related; proficiency in Python, R, SQL
Work EnvironmentAI development teams, R&D labs, tech companiesData analysis teams, research departments, consulting firms
Industry UsageTech, AI startups, research institutionsFinance, healthcare, marketing, tech
Common Search/ComparisonYesYes

While both roles require strong Python skills and familiarity with data analysis, Senior Python Ai focuses more on developing AI models and algorithms, whereas Data Scientists analyze data to generate insights. The Senior Python Ai role emphasizes AI frameworks and machine learning deployment, while Data Scientists often work with statistical analysis and data visualization.

What are the most commonly searched types of Python Ai jobs in Washington, DC? The most popular types of Python Ai jobs in Washington, DC are:
What job categories do people searching Senior Python Ai jobs in Washington, DC look for? The top searched job categories for Senior Python Ai jobs in Washington, DC are:
Senior Python Engineer

Senior Python Engineer

Slingshot Aerospace

Washington, DC • Remote

Other

Posted 12 days ago


Job description

Meet Slingshot 

At Slingshot Aerospace, we're on a mission to make space safer and more secure for everyone. Our work directly impacts global security, disaster response, climate monitoring, and the critical infrastructure that connects our world. We're a team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software. We move fast, we're not afraid to fail, and we believe the best ideas can come from anywhere-whether you're in engineering, sales, product, or operations. If you want to work on something that truly matters, with people who care deeply about the impact we're making and help shape the future of an industry that's just getting started, you're in the right place. 

What You'll Be Launching 

Hiring for two Senior Python Engineers to help architect and build secure, scalable, high-performance data processing and intelligent application platforms in the Washington DC-Baltimore area. Work is mostly done remotely but regular site visits in the DC area are required. 

Requires deep expertise in Python, FastAPI, distributed event-driven systems, MongoDB, and in-memory data technologies such as Redis. The engineer will play a key role in system architecture, development of production-grade services and pipelines, and implementation of best practices across data ingestion, transformation, streaming, AI integration, and secure software delivery. Experience with Retrieval-Augmented Generation (RAG) systems and Agentic AI workflows is highly desirable.

This team is actively re-platforming a mission-critical production data pipeline from a legacy first-generation architecture into a modern, cloud-native, event-driven platform. These are newly created positions-not backfills-established specifically to expand the engineering team responsible for designing and building the next-generation system alongside an experienced group of senior engineers and architects.

This is a highly hands-on engineering role within a small, senior-level team focused on re-architecting a high-throughput, mission-critical data platform. Engineers will work across several high-impact initiatives, including replacing tightly coupled synchronous processing patterns with asynchronous, event-driven microservices and defining the service boundaries, repository structure, and engineering standards that will support the platform long term. This is a true greenfield modernization effort.

Candidates joining at this stage will have direct influence over architecture decisions, service ownership, development standards, and platform strategy. The environment combines modern cloud-native technologies with a serious compliance and security posture, including AWS GovCloud, FastAPI-based Python services, managed AWS infrastructure, Kubernetes with KEDA autoscaling, and Datadog observability. Engineers looking to work at the intersection of advanced distributed systems, cloud-native engineering, and government-grade security will find a strong fit in this opportunity.

Your Mission (Should you choose to accept it)  

  • Develop Python-based ETL frameworks, orchestration layers, and high-throughput data pipelines.
  • Implement and optimize real-time, event-driven streaming architectures using Kafka and/or RabbitMQ.
  • Build and scale FastAPI microservices with strong focus on performance, resilience, security, and observability.
  • Design MongoDB schemas, indexing strategies, and aggregation pipelines with attention to performance.
  • Implement caching layers, session management, and high-speed data access using Redis or similar in-memory stores.
  • Contribute to the design and implementation of RAG pipelines, vector search integrations, and retrieval optimization.
  • Implement Agentic AI workflows using LangChain and Crew AI.
  • Apply Secure SDLC practices across coding, code review, CI/CD, and deployment.
  • Participate in architecture reviews and contribute to engineering standards for distributed systems.
  • Troubleshoot complex data, system, and performance issues in production environments.
  • Support containerization, Kubernetes-native deployment patterns, and AWS cloud integrations.

Pre-flight Checklist 

  • Expert-level Python experience across ETL, microservices, and distributed data processing.
  • Strong FastAPI development and optimization experience.
  • Production experience with Kafka and/or RabbitMQ.
  • Strong MongoDB expertise: schema design, indexing, aggregation, sharding/replication.
  • Experience with in-memory databases such as Redis.
  • Hands-on experience implementing vector search or RAG-based retrieval pipelines.
  • Experience with agent-driven AI architectures and LLM-powered automation workflows.
  • Strong Linux proficiency and experience with Docker/Kubernetes.
  • Demonstrated ability to debug complex distributed or high-scale systems.
  • Hands-on AWS experience across compute, networking, and data services.
  • Proven application of Secure SDLC and secure engineering patterns.
  • Bachelor's or advanced degree in CS, Engineering, or related field.

Strong preference for candidates with Active Top Security Clearance with SCI Eligibility 

Location: Washington DC Metro Area 

Salary: $150,000 - $220,000, equity and benefits