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Python Ai Jobs in Washington (NOW HIRING)

SmartIPlace

Java/J2EE Developer

Mclean, VA · On-site

$51.50 - $66.75/hr

Snowflake, Python, AI research, and financial background. Schedule: Standard Shortlisting Deadline: 07/27 Interview Information: Rounds: 2 rounds Duration: 30 minutes | 60 minutes Interview Type: 1st ...

Nastech Global

Senior AI/ML/Python Engineer

Reston, VA · On-site

Job Title: Senior AI/ML/Python Engineer Location: Onsite in Reston, VA - 3 days a week Job Type: Contract Top Skills Details 7-10 years of experience working as a Python/ML Engineer with strong ...

Edge Global

AI/ML with Python and AWS

Reston, VA · On-site

Job Title : AI/ML with Python and AWS Location : Reston, VA (Local Only) Duration : Full Time MOI: Video + In-Person - We are looking for an experienced AI/ML with Python and AWS . The ideal ...

Edge Global

Python Developer with AI/ML

Reston, VA · On-site

$52.25 - $72/hr

Python Developer with AI/ML Location : Reston, VA (Local Only) Duration : Long Term Contract MOI: Video + In-Person Visa: W2 Consultant Only - We are looking for an experienced Python Developer. The ...

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How much do python ai jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for python ai in Washington is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $54.71 and $75.43 per hour, depending on experience, location, and employer.

What is a Python AI?

A Python AI job involves developing, implementing, and optimizing artificial intelligence models using Python. Professionals in this role work with machine learning frameworks like TensorFlow, PyTorch, and scikit-learn to build automation, predictive analytics, and AI-driven solutions. Responsibilities may include data preprocessing, model training, fine-tuning algorithms, and deploying AI models into production. These roles are common in industries like healthcare, finance, and tech, where AI is used for tasks such as natural language processing, computer vision, and recommendation systems.

What does a Python AI do?

As a Python AI professional, your day-to-day responsibilities usually involve designing, developing, and testing machine learning models, cleaning and analyzing data, and implementing data pipelines. You’ll likely collaborate closely with data scientists, software engineers, and product managers to integrate AI solutions into real-world applications. Regular tasks also include code review, documentation, and participating in team meetings to review progress and brainstorm solutions to technical challenges. These activities not only foster collaboration but also ensure high-quality, scalable AI products.

What skills and qualifications are needed for a Python AI?

To thrive as a Python AI professional, you need strong programming skills in Python, a solid understanding of machine learning algorithms, data structures, and often a degree in computer science or a related field. Proficiency with libraries like TensorFlow, PyTorch, scikit-learn, and experience using version control systems such as Git are typically required, while certifications in AI or data science can be advantageous. Analytical thinking, problem-solving abilities, and effective communication skills help you interpret results and collaborate with multidisciplinary teams. These competencies enable the development, deployment, and optimization of AI-driven solutions in a fast-evolving technical landscape.

Can you do AI with Python?

Python AI refers to roles involving the development and implementation of artificial intelligence using Python programming. These jobs typically require knowledge of machine learning libraries like TensorFlow or PyTorch, data analysis skills, and experience with algorithms. Python's simplicity and extensive ecosystem make it a popular choice for AI development in various industries.

What are the most commonly searched types of Python Ai jobs in Washington?

The most popular types of Python Ai jobs in Washington are:

What are popular job titles related to Python Ai jobs in Washington?

For Python Ai jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Python Ai jobs in Washington look for?

The top searched job categories for Python Ai jobs in Washington are:

Python Ai jobs near you
Infographic showing various Python Ai job openings in Washington as of August 2026, with employment types broken down into 74% Full Time, 17% Part Time, 2% Temporary, and 7% Contract. Highlights an 60% Physical, 4% Hybrid, and 36% Remote job distribution, with an average salary of $138,100 per year, or $66.4 per hour.

Python/AI Full Stack Developer

Ashburn, VA • On-site

Elite IT Solutions inc
Software Development • 1 - 10 employees
Learn more about Elite IT Solutions incexternal

Other

Posted 20 days ago

Job description

Hi,
Please find the job description below
Role: Python/AI Full Stack Developer
Location: Remote
Job Description
•    The Senior Full-Stack Engineer is a hands-on, deeply technical position responsible for designing, building, and deploying cutting-edge Generative AI software and multi-agent systems.
•    This role owns the end-to-end implementation of the foundation's intelligent applications, from engineering advanced backend services on Google Cloud Vertex AI utilizing Gemini Enterprise models, to orchestrating complex workflows with Google’s Agent Development Kit (ADK) and connecting enterprise content and data through the Model Context Protocol (MCP).
•    The engineer will also build interactive web user experiences in React and manage structural and semantic vector data in PostgreSQL.
Qualifications
•    Design, develop, and deploy enterprise-scale multi-agent systems using Google’s Agent Development Kit (ADK), including multi-step autonomous workflows, API and tool calling, stateful conversation management, and human-in-the-loop patterns.
•    Build and maintain Model Context Protocol (MCP) clients and servers to provide standardized connectivity between LLM applications, enterprise content repositories, data platforms, APIs, and web services.
•    Design scalable full-stack architectures connecting AI services, application logic, relational and vector data stores, and interactive web applications.
•    Integrate Gemini models through Google Cloud Vertex AI, configuring context management, prompt templates, structured outputs, model behavior, and appropriate safety controls.
•    Develop clean, maintainable, production-grade Python services supporting application logic, AI orchestration, LangChain workflows, and data integration pipelines.
•    Build modern, responsive web applications using React and JavaScript/TypeScript, including interfaces capable of streaming and displaying agent states and model responses.
•    Design and optimize data solutions using PostgreSQL, pgvector, and BigQuery, supporting relational, keyword, semantic vector, and hybrid search use cases.
•    Develop and optimize Retrieval-Augmented Generation (RAG) pipelines that provide LLMs and agents with accurate, relevant enterprise context.
•    Containerize and deploy full-stack AI applications within Google Cloud Platform, incorporating automated testing and modern CI/CD practices.
•    Monitor and optimize token consumption, model selection and routing, semantic caching, application latency, model accuracy, and cloud costs.
•    Implement evaluation and observability capabilities for AI applications, including agent tracing, response quality monitoring, hallucination detection, model drift identification, and dynamic routing evaluation.
•    Implement AI security controls to mitigate risks including prompt injection, sensitive-data leakage, and unauthorized PII exposure.
•    Apply responsible AI engineering practices, including automated validation and evaluation of prompts and model responses for quality, transparency, fairness, and reliability.
•    Work within an Agile delivery environment and independently take solutions from initial design through development, testing, deployment, and production support.
•    Collaborate with architects, engineers, product teams, and other stakeholders to translate business requirements into scalable technical solutions.
Qualifications and Skills
•    6+ years of professional software engineering experience, with a background in full-stack development, software architecture, machine learning engineering, or a related discipline.
•    2+ years of hands-on Generative AI experience, building and deploying enterprise LLM applications, RAG solutions, or agentic/multi-agent systems into production environments.
•    Advanced programming skills in Python, including experience developing production-grade backend applications and services.
•    Strong hands-on experience with Google Cloud Platform (Google Cloud Platform) and Vertex AI.
•    Production experience working with Gemini or comparable enterprise LLM platforms.
•    Practical experience developing agentic AI solutions using Google Agent Development Kit (ADK) or comparable agent orchestration frameworks.
•    Experience implementing or working with Model Context Protocol (MCP) clients and/or servers.
•    Strong understanding of RAG architectures, embeddings, vector search, context management, prompt engineering, and LLM orchestration.
•    Experience with LangChain or similar AI application frameworks.
•    Proficiency with React and modern JavaScript/TypeScript for developing single-page web applications and integrating streaming APIs.
•    Strong knowledge of PostgreSQL, including relational data modeling, advanced querying, and vector indexing/search using pgvector or similar technologies.
•    Experience with BigQuery or comparable cloud data platforms.
•    Working knowledge of Docker, automated testing, CI/CD pipelines, and cloud-native application deployment.
•    Understanding of Generative AI observability, evaluation, security, model performance, token optimization, and cost management.
•    Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related discipline, or equivalent practical experience.
Preferred Skills
•    Experience designing enterprise-scale autonomous or multi-agent AI systems.
•    Strong understanding of agent memory, tool calling, workflow orchestration, and human-in-the-loop architectures.
•    Experience implementing hybrid search combining traditional keyword retrieval and semantic vector search.
•    Familiarity with LLM evaluation frameworks, tracing, hallucination detection, and model quality monitoring.
•    Knowledge of responsible AI practices and security considerations specific to enterprise Generative AI applications.
•    Experience taking AI applications from proof of concept through scalable production deployment.
 

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