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Ai Infrastructure Engineer Jobs in Washington (NOW HIRING)

AI Infrastructure Engineer

Chantilly, VA

$110K - $144K/yr

AI Infrastructure Engineer Top Secret or TS/SCI is required to start $200K to $250K Chantilly, VA What You'll Do * Deploy and optimize self-hosted LLM inference servers (vLLM, Ollama, and similar)

Software Engineer (AI Infrastructure)

Columbia, MD · On-site

$170K - $201K/yr

Overview BigBear.ai is seeking a S oftware Engineer to support our AI infrastructure team. In this role, you'll help build and maintain the platform that provides the foundation for the customer's AI ...

Software Engineer (AI Infrastructure)

Columbia, MD · On-site

$170K - $201K/yr

Overview BigBear.ai is seeking a S oftware Engineer to support our AI infrastructure team. In this role, you'll help build and maintain the platform that provides the foundation for the customer's AI ...

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Showing results 1-20

Ai Infrastructure Engineer information

See Washington salary details

$52.7K

$143.9K

$206.1K

How much do ai infrastructure engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for ai infrastructure engineer in Washington is $143,915.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,800.00 and $159,700.00 per year, depending on experience, location, and employer.

How much do AI infrastructure engineers make?

AI infrastructure engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and hardware may earn higher salaries, often exceeding $180,000.

What does a typical day look like for an AI infrastructure engineer?

A typical day for an AI Infrastructure Engineer often involves designing and maintaining the underlying systems that support machine learning and AI workloads, such as setting up scalable cloud environments, automating workflows with CI/CD pipelines, and troubleshooting performance bottlenecks. You might collaborate closely with data scientists and software engineers to ensure seamless integration between AI models and production infrastructure. Daily activities can include writing and reviewing infrastructure-as-code, monitoring system health, and responding to incidents or scaling requests as needed. This role offers a dynamic mix of hands-on technical work, problem-solving, and teamwork, providing opportunities to refine your skills and contribute meaningfully to cutting-edge AI projects.

What are the key skills and qualifications needed to thrive as an AI infrastructure engineer?

To thrive as an AI Infrastructure Engineer, a strong background in computer science, cloud computing, and distributed systems is typically required, often supported by a degree in a related field. Familiarity with tools like Kubernetes, Docker, TensorFlow, and cloud platforms (AWS, Azure, or GCP), along with certifications in cloud technologies or DevOps, is highly valuable. Strong problem-solving abilities, collaboration, and effective communication skills are essential to excel within multidisciplinary engineering teams. These competencies ensure the reliable deployment, scaling, and optimization of AI workloads in dynamic production environments.

What does an AI infrastructure engineer do?

An AI Infrastructure Engineer designs, builds, and maintains the computing systems that support AI and machine learning workloads. They manage cloud services, optimize hardware and software performance, and ensure scalability for AI models. Their work involves configuring GPUs, CPUs, storage, and networking, as well as automating workflows with DevOps and MLOps tools. They collaborate with data scientists and engineers to streamline AI development and deployment. Their goal is to create reliable, efficient, and scalable AI infrastructure.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in Washington? The most popular types of Ai Infrastructure Engineer jobs in Washington are:
What job categories do people searching Ai Infrastructure Engineer jobs in Washington look for? The top searched job categories for Ai Infrastructure Engineer jobs in Washington are:
Infographic showing various Ai Infrastructure Engineer job openings in Washington as of July 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $143,915 per year, or $69.2 per hour.

Lead AI Infrastructure Engineer

Staffed4U

Annapolis Junction, MD

$293K - $306K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago


Job description

Lead AI Infrastructure Engineer

Location: Annapolis Junction, MD
Clearance: TS/SCI with Polygraph required
Work Type:
On-site
Salary: $293,000-$306,000

Position Overview

We are seeking an experienced Lead AI Infrastructure Engineer to provide technical leadership for the design, deployment, and operation of enterprise artificial intelligence and machine learning platforms. This role will lead the development and sustainment of critical AI infrastructure components, with a focus on scalable model deployment, platform reliability, and support for AI-enabled applications and services.

The successful candidate will combine hands-on engineering expertise with team leadership responsibilities, serving as a technical lead for platform initiatives while supporting the professional development of engineering staff. This position requires strong cloud engineering, platform architecture, and organizational leadership skills to drive innovation, operational excellence, and technology adoption across multiple teams.


Key Responsibilities
  • Design, implement, and optimize infrastructure supporting large-scale AI model deployment and inference services.
  • Lead the development, deployment, and maintenance of production AI applications and platform services.
  • Serve as the technical lead for AI infrastructure initiatives, coordinating activities across engineering teams and stakeholders.
  • Provide mentorship, coaching, and professional development support to engineering team members.
  • Support team operations, resource planning, and administrative coordination activities.
  • Define technical solutions for complex and evolving requirements.
  • Establish and maintain technical standards, policies, governance processes, and engineering best practices.
  • Drive adoption of emerging technologies, automation capabilities, and platform modernization initiatives.
  • Design, implement, and oversee monitoring, logging, alerting, and observability solutions.
  • Ensure the reliability, availability, scalability, performance, and security of AI platform components.
  • Communicate technical strategies, project status, and recommendations to stakeholders at multiple organizational levels.
  • Lead troubleshooting, root cause analysis, and continuous improvement efforts for production systems.

Required QualificationsEducation and Experience
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related technical discipline and twelve (12) years of relevant experience; OR
  • Four (4) additional years of directly related experience may be substituted for the degree requirement.
Technical Qualifications
  • Extensive experience designing, building, deploying, and operating enterprise-scale production systems.
  • Deep expertise in systems integration across diverse technologies, platforms, and cloud environments.
  • Hands-on experience designing, deploying, and managing cloud infrastructure within Amazon Web Services (AWS).
  • Advanced experience administering and deploying applications using Kubernetes.
  • Strong software development skills using Python.
  • Experience implementing and scaling observability solutions using technologies such as:
    • Application Performance Monitoring (APM) tools
    • OpenTelemetry
    • Grafana
    • Prometheus
  • Experience developing and maintaining highly available, resilient, and secure distributed systems.
  • Proven ability to lead complex technical initiatives and influence organizational technology adoption.
  • Experience establishing technical standards, governance frameworks, and engineering policies.
  • Excellent communication, stakeholder engagement, and leadership skills.
  • Demonstrated ability to balance hands-on engineering responsibilities with leadership and team coordination duties.

Preferred Qualifications
  • Experience supporting AI model serving and inference platforms.
  • Experience integrating large language models (LLMs) and generative AI technologies into enterprise applications.
  • Experience with AI orchestration and workflow frameworks, including LangChain or similar technologies.
  • Knowledge of vector databases, embeddings, and semantic search technologies.
  • Experience implementing Retrieval-Augmented Generation (RAG) architectures.
  • Experience with distributed computing, high-performance computing, or large-scale processing environments.
  • Demonstrated success leading technical transformation, modernization, or organizational change initiatives.
  • Familiarity with autonomous agent frameworks and emerging AI technologies.

Knowledge, Skills, and Abilities
  • Strong leadership and technical decision-making capabilities.
  • Expertise in cloud-native architecture, platform engineering, and distributed systems.
  • Ability to balance reliability, scalability, security, and performance requirements.
  • Strong analytical and problem-solving skills.
  • Ability to establish technical direction and influence engineering organizations.
  • Excellent written and verbal communication skills.
  • Strong mentoring, coaching, and team development abilities.
  • Ability to work effectively across technical and non-technical stakeholder groups.
  • Strong organizational skills and attention to detail.

Benefits

This position includes a competitive and flexible benefits package, including:

  • Medical
    Employer pays 100% of the monthly premium for the employee and 80% for the employee’s dependents.

  • Health Savings Account (HSA)
    Save for all medical, dental, vision and prescription expenses by contributing pre-tax money to an HSA account. Employer contributes 50% of the annual deductible (prorated to start date).

  • Dental and Vision
    Employer pays 100% of the monthly premium for the employee and 80% for dependents.

  • Life Insurance
    100% company-paid Life and Accidental Death & Dismemberment (AD&D) coverage offered to all full-time employees.

  • Short-Term Disability
    100% company-paid short-term disability. This benefit pays out 60% of earnings, with a $1,500 maximum for up to 12 weeks.

  • Retirement Plan
    Automatic 6% of salary contributed to the company 401(k) plan, fully vested. Employee match encouraged but not required.

  • Paid Time Off (PTO) & Holidays
    5–6 weeks of PTO based on tenure with the company, in addition to 11 paid holidays.

  • Tuition Reimbursement
    $5,000 annually for courses directly related to job role and responsibilities.

  • Training Reimbursement
    Paid training, certification courses, and conferences to support employee career growth.


We do not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.