MLOps Jobs in District of Columbia.
All active MLOps roles based in District of Columbia.
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Senior AI Solutions Architect
AI Office Lead - Senior AI Solutions Architect
NTT DATA is a team of more than 139,000 diverse professionals operating in more than 50 countries worldwide. Our sectors of activity include telecommunications, finance, industry, utilities, energy, public administration, and health.
Our mission? Offer technological solutions, business, strategy, development, and application maintenance while being a benchmark in consulting. Thanks to the collaboration between teams, the human quality of our people, and the fact that we do not conform to what is established, we always seek innovation that brings us closer to the future.
Our essence has led us to the forefront of technology, breaking paradigms and providing solutions that truly respond to each client's needs. Our talent has led us to be one of the top six technology companies in the world.
Because #Greattech, needs #GreatPeople, like you
NTT Data seeks high-achieving team players who quickly adapt to new challenges and entrepreneurial ventures. We are looking for a Senior AI Solutions Architect to work with our global client in Washington, D.C. This role will require an onsite presence at our client location.
Location: Washington D.C. onsite is highly preferred BUT open to candidates from Peru, Mexico, Brazil, or Chile who can work in the DC time zone**
Focus: AI Platform Architecture, Orchestration & Enterprise Integration
Experience Level: Senior (7+ years)
Role Overview
The Senior AI Solutions Architect is a senior technical authority responsible for designing, assessing, and shaping the organization’s AI platform landscape. This role focuses on AI orchestration frameworks, multi-agent systems, enterprise integration, and solution architecture, while providing architectural governance and technical leadership for AI initiatives across the organization.
The role is hands-on and architecture-led, with a strong emphasis on application rationalization, technology assessment, and proof-of-concept (PoC) execution to inform strategic platform and investment decisions. Acting as a bridge between strategy and engineering, the role ensures AI solutions are architecturally sound, interoperable, secure, and scalable in complex, regulated, and mission-driven environments.
Background & Environment
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Proven experience as a senior architect or technical lead within AI, data, or digital platforms.
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Experience working in large, federated, or matrixed organizations, including public sector, healthcare, or international institutions.
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Strong background operating in environments with governance, compliance, interoperability, and cross-domain integration requirements
Key Responsibilities
AI Architecture & Platform Strategy
- Serve as the senior solutions architect for AI platforms, orchestration frameworks, and agent-based systems
- Define and evolve enterprise AI architecture standards covering:
- Data ingestion and integration
- Model and agent orchestration
- Deployment, runtime, and integration patterns
- Assess and rationalize existing applications, data assets, and platforms to identify AI enablement opportunities and technical debt
AI Orchestration, Agents & Integration
- Design and evaluate AI orchestration frameworks, including multi-agent and tool-based architectures
- Lead architecture decisions for agent-based systems, including interaction models, control flows, guardrails, and observability
- Define enterprise integration patterns between AI systems and core business applications, APIs, data platforms, and workflows
PoCs, Assessments & Decision Support
- Lead and oversee proof-of-concept development to validate architectural approaches, tools, and platforms
- Conduct structured technology evaluations and comparisons to inform build vs. buy and platform selection decisions
- Translate PoC outcomes into clear architectural recommendations and roadmaps for production deployment
Governance & Architectural Assurance
- Provide architectural oversight to ensure alignment between AI solutions and governance, security, Responsible AI, and data policies
- Review solution designs for compliance with architectural standards, operational readiness, and scalability
- Act as a technical escalation point for complex integration, performance, and design challenges
Collaboration & Enablement
- Partner closely with engineering teams, product owners, security, and governance stakeholders to guide solution design
- Mentor architects and senior engineers on AI architecture patterns, agent design, and orchestration best practices
- Communicate architectural concepts and tradeoffs clearly to both technical and non-technical stakeholders
Required Technical Skills & Expertise
AI Orchestration & Agent Architectures
- Strong experience with AI orchestration frameworks and multi-agent systems
- Hands-on knowledge of agent frameworks (e.g., LangChain, LangGraph, MCP-style architectures)
- Experience designing RAG-based systems, vector search, grounding, and tool invocation strategies
AI & Machine Learning Systems
- Experience architecting ML, deep learning, and Generative AI solutions in enterprise settings
- Strong proficiency with Python-based AI frameworks (e.g., PyTorch, TensorFlow)
- Understanding of model lifecycle management and production deployment considerations
Data & Integration Architecture
- Experience designing enterprise data architectures that support AI workloads (data lakes, lakehouse patterns)
- Knowledge of data integration, APIs, event-driven architectures, and streaming pipelines
- Familiarity with data quality, lineage, metadata, and governance requirements
Cloud & Platform Architecture
- Strong experience architecting AI solutions on cloud platforms, particularly Azure-based AI and data services
- Experience with containerization and cloud-native deployment patterns
- Familiarity with infrastructure-as-code and secure cloud design principles
DevOps, MLOps & Evaluation
- Understanding of MLOps and CI/CD patterns for AI systems
- Experience setting up monitoring, evaluation, and feedback loops for models and agent systems
- Ability to assess operational readiness, cost, and performance of AI solutions.
Preferred Certifications & Training
- Scrum Master or equivalent Agile certification
- Executive-level training in AI Strategy
- NIST AI Risk Management Framework (AI RMF) training
- Microsoft Azure AI Engineer Associate
- Microsoft Azure Solutions Architect Expert
- Microsoft Copilot and Agent Administration Fundamentals
Why NTT Data?
Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.
NTT Data is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. NTT Data is an Equal Opportunity Employer Male/Female/Disabled/Veteran and a VEVRAA Federal Contractor.
Ready to apply?
Apply to NTT DATA, Europe & LATAM, Branch in USA, Inc.
AI Programmer
AI Programmer – MCP Server & Agent Systems
NTT DATA is a team of more than 139,000 diverse professionals operating in more than 50 countries worldwide. Our sectors of activity include telecommunications, finance, industry, utilities, energy, public administration, and health.
Our mission? Offer technological solutions, business, strategy, development, and application maintenance while being a benchmark in consulting. Thanks to the collaboration between teams, the human quality of our people, and the fact that we do not conform to what is established, we always seek innovation that brings us closer to the future.
Our essence has led us to the forefront of technology, breaking paradigms and providing solutions that truly respond to each client's needs. Our talent has led us to be one of the top six technology companies in the world.
Because #Greattech, needs #GreatPeople, like you
NTT Data seeks high-achieving team players who quickly adapt to new challenges and entrepreneurial ventures. We are looking for a AI Programmer to work with our global client in Washington, D.C. This role will require an onsite presence at our client location.
Experience Level: Mid–Senior (4–7+ years)
Focus: AI Agents, MCP Servers, Python Engineering
Location: Washington, D.C. (onsite preferred)
Open to candidates based in Peru, Mexico, Brazil, or Chile who can work in the DC time zone
Role Overview
The AI Programmer – MCP Server & Agent Systems is a hands-on engineering role focused on building, deploying, and maintaining MCP servers and agent-based AI services that integrate with enterprise platforms and data systems.
This role works closely with Senior AI Solutions Architects and platform teams to implement production-ready AI agents, orchestration workflows, and backend services using Python. The ideal candidate is a strong programmer with practical experience implementing AI agent patterns—not just experimenting with them.
Key Responsibilities
MCP Server & Agent Development
- Design, build, and maintain MCP servers that support AI agent execution, tool invocation, and orchestration
- Implement agent-based workflows using Python and modern AI frameworks
- Develop reusable services and APIs to enable agent interaction with enterprise systems and data sources
AI Agent Implementation
- Implement AI agents using frameworks such as LangChain, LangGraph, or MCP-style architectures
- Support RAG-based solutions including vector search, embeddings, and grounding strategies
- Implement guardrails, logging, and error handling for agent reliability and safety
Integration & Deployment
- Integrate AI agents with existing applications, APIs, data platforms, and workflows
- Package and deploy AI services using containerization and cloud-native patterns
- Support CI/CD pipelines for AI services and agent systems
Collaboration & Delivery
- Work closely with AI architects to implement approved designs and PoCs
- Participate in code reviews, testing, and technical documentation
- Support iteration from PoC to production under architectural and governance guidance
Required Technical Skills & Experience
Programming & Engineering
- Strong proficiency in Python
- Experience building backend services, APIs, or microservices
- Familiarity with Git-based workflows and collaborative development
AI Agents & Generative AI
- Hands-on experience implementing AI agents or orchestration workflows
- Experience with frameworks such as LangChain, LangGraph, or similar agent frameworks
- Understanding of LLM-based applications, prompt design, and tool-calling patterns
Data & AI Integration
- Experience working with vector databases, embeddings, and RAG pipelines
- Ability to integrate AI services with structured and unstructured data sources
- Familiarity with data APIs, event-driven systems, or streaming pipelines is a plus
Cloud & DevOps (Preferred)
- Experience deploying services in cloud environments (Azure preferred)
- Familiarity with Docker and cloud-native deployment patterns
- Exposure to CI/CD pipelines and basic MLOps concepts
Why NTT Data?
Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.
NTT Data is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. NTT Data is an Equal Opportunity Employer Male/Female/Disabled/Veteran and a VEVRAA Federal Contractor.
Ready to apply?
Apply to NTT DATA, Europe & LATAM, Branch in USA, Inc.
OVERVIEW
A thriving, mission-driven multimedia organization, NPR produces award-winning news, information, and music programming in partnership with hundreds of independent public radio stations across the nation. The NPR audience values information, creativity, curiosity, and social responsibility – and our employees do too. We are innovators and leaders in diverse fields, from journalism and digital media to IT and development. Every day, our employees and member stations touch the lives of millions worldwide.
Across our organization, we’re building a workplace where collaboration is essential, diverse voices are heard, and inclusion is the key to our success. We are committed to doing the right thing in our journalism and in every role at NPR. This means that integrity, adherence to our ethical standards, and compliance with legal obligations are fundamental responsibilities for every employee at NPR.
Intro to Position
The Lead AI Solutions Engineer, AI Labs, is a foundational role in building NPR's first Generative AI (GAI)-focused product development team. Reporting to the VP of AI Labs, this engineer will be responsible for the technical development and implementation of generative AI solutions. The core mission is to engineer systems that leverage GAI to enhance the quality and actionability of our content metadata, thereby directly supporting the organization's goals of improving content personalization and increasing editorial efficiency. This role involves hands-on work in integrating AI products into core NPR systems, ensuring solutions are scalable, align with ethical guidelines, and are built upon industry best practices. This is a critical opportunity to shape NPR's technical AI adoption and build a new, innovative function.
Responsibilities
- Engineering & Implementation: Design, develop, and deploy scalable Generative AI (GAI) solutions, focusing on enhancing content metadata quality and actionability to meet organizational objectives.
- Architecture & Technical Best Practices: Establish and champion technical best practices for Generative AI systems, including MLOps, RAG architectures, prompt engineering, and model evaluation, ensuring high-quality, maintainable code.
- Cross-functional Development: Collaborate closely with Product Managers, data scientists, software and infrastructure engineers, and relevant subject matter experts to translate product requirements and roadmaps into robust, production-ready AI systems.
- System Optimization & Performance: Implement data-driven methods, A/B testing, and performance monitoring to optimize the efficiency, scalability, and impact of AI models and pipelines.
- Technical Communication: Clearly articulate technical architectures, development progress, and engineering challenges to product and non-technical stakeholders.
- Responsible AI: Integrate ethical AI principles and compliance standards directly into the design and implementation of all AI products, in alignment with company policies.
- Technology Scouting: Research and evaluate emerging AI technologies, frameworks, and industry trends to drive continuous technical innovation within the AI Labs.
The above duties and responsibilities are not an exhaustive list of required responsibilities, duties and skills. Other duties may be assigned, and this job description is subject to change at any time.
Minimum Qualifications
- 8+ years of professional experience in software development, data science, or machine learning engineering, with a focus on building and deploying production systems.
- 2+ years of hands-on experience working with generative AI, machine learning, or data products.
- Expert proficiency in Python and experience creating functional prototypes to validate technical feasibility and user flows.
- Demonstrable understanding and experience building products that leverage Large Language Models, RAG architectures, prompting, function calling, retrieval, vector databases, embeddings, fine-tuning, and model evaluation.
- Familiarity with building and integrating MCP servers and agentic workflows.
- Background in creating QA systems for AI processes and development.
- Excellent communication skills and the ability to clearly articulate technical architectures and challenges to product and non-technical stakeholders.
- A collaborative and respectful approach to work and an ability to adapt quickly to change.
- A deep commitment to the mission of NPR and to the responsible implementation of Generative AI technologies.
Preferred Qualifications
- Experience designing and building highly scalable, production-grade AI/ML pipelines and services.
- Proficiency with cloud platforms, particularly AWS and Google Cloud Platform (GCP) and MLOps tools, particularly MLFlow and Vertex AI.
- Experience with DevOps practices, including CI/CD and enterprise infrastructure-as-code.
- Experience working in media organizations and an understanding of media delivery systems.
Work Location & Requirements
- Hybrid Permitted: This is a hybrid permitted role. Some aspects of this role require duties better performed at an NPR facility. The employee will be required to be in the office at the Washington, D.C. location at least two days a week. The employee must also reside in an NPR-supported location (D.C., MD, or VA).
Job Type
- This is a full-time, exempt position.
Compensation
Salary Range: The U.S. based anticipated salary range for this opportunity is $187,000 - $208,000 plus benefits. The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.
NPR Benefits: NPR offers access to comprehensive benefits for employees and dependents. Regular, full-time employees scheduled to work 30 hours or more per week are eligible to enroll in NPR’s benefits options. Benefits include access to health and wellness, paid time off, and financial well-being. Plan options include medical, dental, vision, life/ accidental death and dismemberment, long-term disability, short-term disability, and voluntary retirement savings to all eligible NPR employees.
Does this sound like you? If so, we want to hear from you.
#LI-HYBRID
NPR is an Equal Opportunity Employer. NPR is committed to being an inclusive workplace that welcomes diverse and unique perspectives, all working toward the same goal – to create a more informed public. Qualified applicants receive consideration for employment without regard to race, color, ethnicity, national origin, ancestry, age, religion, religious belief, sex (including pregnancy, childbirth and related medical conditions, lactation, and reproductive health decisions), sexual orientation, gender, gender identity or expression, transgender status, gender non-conforming status, intersex status, sexual stereotypes, nationality, citizenship status, personal appearance, marital status, family status, family responsibilities, military status, veteran status, mental and physical disability, medical condition, genetic information, genetic characteristics of yourself or a family member, political views and affiliation, unemployment status, protective order status, status as a victim of domestic violence, sexual assault, or stalking, or any other basis prohibited under applicable law.
If you are a person with a disability needing assistance with the application process, please reach out to employeerelations@npr.org.
You may read NPR’s privacy policy to learn about how NPR may handle information you submit with any application.
Want more NPR? Explore the stories behind the stories on our NPR Extra blog. Get social with NPR Extra on Facebook and Instagram. Find more career opportunities at NPR.org/careers.
Ready to apply?
Apply to NPR