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Gen Ai Developer Jobs in Washington (NOW HIRING)

Cognizant

Gen AI Developer/Lead

Washington, DC · On-site

$158K - $194K/yr

Job Summary We are seeking a highly skilled and innovative Senior AI/ML Engineer with strong expertise in Python, PySpark, Azure Machine Learning, Generative AI, and Full Stack Development to design ...

UNISSANT

Senior AI Systems Architect

Ashburn, VA · On-site

AI/ML & Gen-AI Solution Engineering * Lead design and deployment of AI/ML and Gen-AI solutions including: * RAG architectures * Agentic AI frameworks * LLM orchestration * Computer Vision * Image ...

Unissant

Senior AI Systems Architect

Ashburn, VA · On-site

$145K - $208K/yr

AI/ML & Gen-AI Solution Engineering * Lead design and deployment of AI/ML and Gen-AI solutions including: * RAG architectures * Agentic AI frameworks * LLM orchestration * Computer Vision * Image ...

KLDiscovery

AI Architect

Mclean, VA · On-site

$190K - $230K/yr

As AI Architect, you'll own the north star for gen AI and ML engineering at KLDiscovery and build alongside the team to make it real. This is one of the most interesting AI problem sets in enterprise ...

Unissant

Senior AI Systems Architect

Ashburn, VA · On-site

$145K - $208K/yr

Required:12+ years of experience in enterprise architecture, AI/ML engineering, cloud modernization, or advanced analytics solutions.5+ years designing and implementing AI/ML or Gen-AI solutions in ...

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How much do gen ai developer jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for gen ai developer in Washington is $51.29, according to ZipRecruiter salary data. Most workers in this role earn between $26.68 and $62.07 per hour, depending on experience, location, and employer.

What is a Gen AI developer?

A Gen AI Developer is a professional who designs, builds, and deploys applications using generative artificial intelligence models, such as large language models (LLMs) or image generators. They work with AI frameworks and APIs to create solutions that can generate text, images, code, or other content based on user input. Gen AI Developers often need skills in programming, machine learning, and prompt engineering, and they play a key role in building innovative AI-powered applications across various industries.

What are the key skills and qualifications needed to thrive as a Gen AI developer, and why are they important?

To thrive as a Gen AI Developer, you need a strong background in computer science, machine learning, and deep learning frameworks, often supported by a degree in a related field. Proficiency with tools such as Python, TensorFlow or PyTorch, and experience with cloud platforms like AWS or Azure, as well as relevant certifications, are commonly required. Critical thinking, creativity, and effective communication are essential soft skills for solving complex problems and collaborating with cross-functional teams. These competencies are vital for developing innovative AI solutions that drive business value and maintain technological competitiveness.

What are some common challenges Gen AI developers face when deploying models into production environments?

Gen AI Developers often encounter challenges such as ensuring model scalability, maintaining data privacy, and managing high computational requirements when deploying generative AI models. Integrating models with existing systems and monitoring for model drift or bias are also critical concerns. Close collaboration with DevOps, data engineering, and security teams is essential to build robust deployment pipelines and maintain reliable performance in real-world applications.

What is the difference between Gen Ai Developer vs Machine Learning Engineer?

AspectGen Ai DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with AI frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentTech companies, AI startups, research labs focusing on generative AITech firms, data-driven companies, research institutions working on ML models
Employer & Industry UsagePrimarily in AI development, focusing on generative models and AI applicationsBroader industry use, including predictive modeling, data analysis, and automation

While both roles involve AI and machine learning skills, Gen AI Developers specialize in creating generative AI models like chatbots and content generators, whereas Machine Learning Engineers develop a wide range of ML algorithms for various applications. The roles often overlap but differ in focus and project types.

How can I become a Gen AI developer?

To become a Gen AI developer, you should gain strong programming skills in languages like Python, learn machine learning frameworks such as TensorFlow or PyTorch, and develop expertise in natural language processing and large language models. Building a portfolio of AI projects and obtaining relevant certifications can also enhance your qualifications for this role.

Is a Gen AI Developer a promising career?

A Gen AI Developer is a growing role focused on creating and improving generative artificial intelligence systems, often requiring skills in machine learning, deep learning, and programming languages like Python. The demand for such developers is increasing as AI applications expand across industries, making it a promising career with strong job growth prospects.

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

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

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

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

What cities in Washington are hiring for Gen Ai Developer jobs?

Cities in Washington with the most Gen Ai Developer job openings:

Gen Ai Developer jobs near you
Infographic showing various Gen Ai Developer 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 $106,690 per year, or $51.3 per hour.

Gen AI Developer/Lead

Washington, DC • On-site

Cognizant Technology Solutions
See more jobs at Cognizant Technology Solutionsexternal

$158K - $194K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago

Cognizant rating

7.0

Company rating: 7.0 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

Job description

No Visa Transfer/c2c/Sponsorship available now or in the future, for this role
Job Summary
We are seeking a highly skilled and innovative Senior AI/ML Engineer with strong expertise in Python, PySpark, Azure Machine Learning, Generative AI, and Full Stack Development to design and deliver advanced analytics and AI-driven solutions for global investment banking and brokerage operations.
The ideal candidate will combine deep technical expertise in machine learning, distributed computing, cloud-native AI platforms, and modern AI frameworks such as LangChain, LangGraph, RAG, Agentic AI Frameworks, FastAPI, and Azure OpenAI Service. This role requires close collaboration with business stakeholders to transform complex financial data into actionable insights that improve decision-making, reduce operational risk, and enhance operational efficiency.
Key Responsibilities
Machine Learning & Advanced Analytics
  • Design, develop, and deploy advanced machine learning models using Python and PySpark to analyze large-scale financial datasets and generate actionable business insights.
  • Build predictive, classification, clustering, anomaly detection, forecasting, and risk models supporting investment banking and brokerage functions.
  • Perform rigorous model validation, back-testing, and experimentation using historical and simulated market data.
  • Evaluate and implement appropriate statistical, machine learning, deep learning, and AI techniques based on business requirements and regulatory considerations.
  • Optimize model performance through feature engineering, hyperparameter tuning, algorithm enhancements, and distributed computing techniques.

Generative AI & Agentic Solutions
  • Design and implement enterprise-grade Generative AI solutions using Azure OpenAI Service.
  • Build and deploy Retrieval-Augmented Generation (RAG) applications leveraging vector databases and knowledge retrieval systems.
  • Develop intelligent agent-based systems using LangChain, LangGraph, and Agentic AI frameworks to automate business workflows and enhance decision support.
  • Apply Natural Language Processing (NLP), Large Language Models (LLMs), document intelligence, and conversational AI to streamline surveillance, reporting, compliance, and advisory functions.
  • Ensure safe, responsible, and governed adoption of Generative AI capabilities across the organization.

Python Full Stack Development
  • Design and develop scalable backend services and APIs using FastAPI.
  • Build microservices and AI application frameworks that integrate machine learning and GenAI capabilities into enterprise ecosystems.
  • Develop reusable and maintainable software components following modern software engineering best practices.
  • Implement API integrations, authentication mechanisms, monitoring, logging, and performance optimization strategies.

Data Engineering & MLOps
  • Design and implement scalable data pipelines and feature engineering workflows using Azure Machine Learning and cloud-native services.
  • Build reusable data products and machine learning components supporting multiple analytics and AI initiatives.
  • Partner with Data Engineering teams to operationalize machine learning models and AI applications.
  • Establish model monitoring, retraining strategies, experiment tracking, and lifecycle management processes.
  • Ensure solutions are secure, reliable, scalable, and production-ready.

Cloud & Azure AI Platform
  • Develop end-to-end ML and AI solutions using:
    • Azure Machine Learning
    • Azure OpenAI Service
    • Azure Data Lake
    • Azure Databricks
    • Azure Storage Services
    • Azure DevOps
  • Manage model deployment, monitoring, governance, and operationalization on Azure platforms.
  • Support enterprise-scale AI and analytics workloads while maintaining compliance and security standards.

Business Collaboration
  • Collaborate with product owners, business analysts, operations teams, and technology stakeholders to define high-value data science initiatives.
  • Translate complex investment banking and brokerage business challenges into measurable analytical solutions.
  • Present recommendations and analytical findings to both technical and non-technical audiences.
  • Drive adoption of AI and machine learning solutions through effective communication and stakeholder engagement.

Governance & Responsible AI
  • Promote responsible AI practices by evaluating model fairness, explainability, bias, security, and data quality.
  • Document assumptions, risks, methodologies, and limitations in a transparent and accessible manner.
  • Ensure adherence to regulatory requirements, model governance frameworks, and enterprise AI policies.

Leadership & Mentoring
  • Mentor junior data scientists, machine learning engineers, and developers.
  • Promote best practices in software development, experimentation, MLOps, AI engineering, and model governance.
  • Contribute to a culture of innovation, continuous learning, and technical excellence.

Required Qualifications
Technical Skills
  • 8+ years of experience in Data Science, Machine Learning, AI Engineering, or related fields.
  • Expert-level proficiency in Python and PySpark for large-scale data processing and model development.
  • Strong experience with:
    • FastAPI
    • REST APIs
    • Microservices Architecture
    • Object-Oriented Programming
    • Software Engineering Best Practices
  • Hands-on experience with:
    • LangChain
    • LangGraph
    • RAG Architectures
    • Agentic AI Frameworks
    • LLM Application Development
  • Strong expertise in:
    • Azure Machine Learning
    • Azure OpenAI Service
    • Azure Databricks
    • Azure Data Lake
    • MLOps and CI/CD Practices
  • Experience developing and deploying enterprise-grade AI/ML solutions in cloud environments.

Machine Learning & AI
  • Deep understanding of:
    • Supervised Learning
    • Unsupervised Learning
    • Deep Learning
    • Ensemble Methods
    • NLP
    • Time-Series Forecasting
    • Anomaly Detection
    • Risk Modeling
  • Strong understanding of model evaluation, feature engineering, experimentation, validation, and explainability.

Domain Experience
  • Prior experience supporting:
    • Investment Banking
    • Capital Markets
    • Brokerage Operations
    • Trade Surveillance
    • Risk Management
    • Front Office or Middle Office Functions
  • Understanding of financial products, market data, and regulatory expectations is highly desirable.

Soft Skills
  • Excellent communication and stakeholder management skills.
  • Ability to explain complex technical topics to non-technical audiences.
  • Strong analytical and problem-solving capabilities.
  • Experience working effectively within distributed and hybrid teams.

Preferred Qualifications
  • Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, or ChromaDB.
  • Knowledge of containerization technologies including Docker and Kubernetes.
  • Experience with CI/CD pipelines and DevOps practices.
  • Exposure to Responsible AI, Model Risk Management, and AI governance frameworks.
  • Azure certifications in AI, Data Science, or Machine Learning.

*Please note this role is not able to offer visa transfer or sponsorship now or in the future*
We're excited to meet people who share our mission and who can make an impact in a variety of ways. Don't hesitate to apply-even if you only meet the minimum requirements. Think about your transferable experiences and unique skills that make you stand out.
Salary and Other Compensation:
The annual salary for this position is between $100,000 $ 156,000+ depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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