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Senior Ai Infrastructure Engineer Jobs in Washington

Senior AI Platform Engineer

Arlington, VA · On-site

$120K - $165K/yr

Arlington Summary The Senior AI Platform Engineer is responsible for building and operating the infrastructure that powers Venture Global's AI Engineering function. This role designs, stands up, and ...

Senior AI Platform Engineer

Arlington, VA · On-site

$120K - $165K/yr

Arlington Summary The Senior AI Platform Engineer is responsible for building and operating the infrastructure that powers Venture Global's AI Engineering function. This role designs, stands up, and ...

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)

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)

Senior AI Engineer

Annapolis Junction, MD

$106K - $146K/yr

Senior AI Engineer ***(Active Clearance with a Polygraph is Required) We're on multiple contracts ... Experience with distributed systems or large-scale AI infrastructure Requirements: * Must be a U.S ...

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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Senior Ai Infrastructure Engineer information

What does a senior AI infrastructure engineer do?

A Senior AI Infrastructure Engineer is responsible for designing, building, and maintaining the large-scale computing systems that support artificial intelligence (AI) and machine learning (ML) workloads. They work on optimizing data pipelines, managing cloud or on-premise infrastructure, ensuring scalability, and enabling efficient training and deployment of AI models. These professionals collaborate closely with data scientists, software engineers, and IT teams to create robust, high-performance environments that support the rapid development and deployment of AI solutions.

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

To thrive as a Senior AI Infrastructure Engineer, you need deep expertise in computer science, cloud computing, distributed systems, and AI/ML frameworks, often supported by a relevant degree and significant experience. Proficiency with tools such as Kubernetes, Docker, TensorFlow, PyTorch, and cloud platforms like AWS or Azure—as well as experience with CI/CD pipelines—is typically required. Strong problem-solving abilities, collaboration, and effective communication are standout soft skills for this role. These competencies are crucial for designing scalable, reliable AI infrastructure that supports complex machine learning workflows and organizational goals.

What are some typical challenges faced by senior AI infrastructure engineers when scaling AI systems for production?

Senior AI Infrastructure Engineers often encounter challenges related to managing large-scale data pipelines, ensuring low-latency model serving, and maintaining system reliability as user demand grows. Balancing resource allocation for compute-intensive workloads, optimizing infrastructure costs, and implementing robust monitoring are common hurdles. Collaboration with data scientists, DevOps, and product teams is crucial to streamline deployment cycles and rapidly address issues as they arise. Mastery of distributed systems and cloud platforms often distinguishes top performers in this role.

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Senior AI Infrastructure Engineer

Staffed4U

Annapolis Junction, MD

$293K - $306K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago


Job description

Senior 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 Senior AI Infrastructure Engineer to support the design, deployment, and operation of enterprise artificial intelligence and machine learning platforms. This role will be responsible for developing and maintaining scalable infrastructure that enables the delivery of AI-powered applications and services across the organization.

The successful candidate will independently design, implement, and operate cloud-native infrastructure components while supporting modern AI technologies, distributed systems, and production service environments. This position requires strong expertise in platform engineering, cloud technologies, automation, observability, and software development.


Key Responsibilities
  • Design, implement, and optimize infrastructure supporting AI model deployment and inference at scale.
  • Develop, maintain, and support production AI services and applications.
  • Collaborate with stakeholders and engineering teams to define technical solutions for evolving business and operational requirements.
  • Design and implement scalable, reliable, and maintainable platform architectures.
  • Drive adoption of emerging technologies, engineering best practices, and automation solutions.
  • Implement monitoring, logging, alerting, and observability capabilities for platform services.
  • Automate infrastructure provisioning, configuration, and lifecycle management using Infrastructure-as-Code (IaC) methodologies.
  • Ensure high availability, reliability, performance, and scalability of platform services.
  • Support the secure deployment and operation of AI systems and associated data environments.
  • Contribute to system architecture reviews, platform modernization efforts, and operational support activities.
  • Provide technical guidance, knowledge sharing, and mentorship to engineering team members.
  • Participate in troubleshooting, root cause analysis, and continuous improvement initiatives.

Required QualificationsEducation and Experience
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related technical discipline and eight (8) years of relevant experience; OR
  • Four (4) additional years of directly related experience may be substituted for the degree requirement.
Technical Qualifications
  • Demonstrated experience building, deploying, and maintaining enterprise-scale production systems.
  • Experience designing and supporting high-volume web applications and distributed service architectures.
  • Strong background in systems integration across diverse technologies, platforms, and cloud environments.
  • Hands-on experience designing, deploying, and operating cloud infrastructure in Amazon Web Services (AWS).
  • Experience administering and deploying applications using Kubernetes.
  • Strong software development skills using Python.
  • Experience implementing observability and monitoring solutions using technologies such as:
    • Application Performance Monitoring (APM) tools
    • OpenTelemetry
    • Grafana
    • Prometheus
  • Experience developing and maintaining Continuous Integration and Continuous Deployment (CI/CD) pipelines.
  • Knowledge of DevOps principles, automation practices, and modern software delivery methodologies.
  • Demonstrated ability to lead technical initiatives and influence engineering practices across teams.
  • Ability to operate effectively in dynamic environments with evolving requirements.
  • Excellent written and verbal communication skills.

Preferred Qualifications
  • Experience supporting AI model deployment, serving, and inference platforms.
  • Experience integrating generative AI and large language model (LLM) technologies into enterprise applications.
  • Experience with AI workflow orchestration frameworks, including LangChain or similar technologies.
  • Knowledge of vector databases, embedding technologies, and semantic search solutions.
  • Experience implementing Retrieval-Augmented Generation (RAG) architectures.
  • Experience with distributed computing, high-performance computing, or large-scale processing environments.
  • Familiarity with autonomous agent frameworks and emerging AI technologies.

Knowledge, Skills, and Abilities
  • Strong cloud engineering and platform architecture expertise.
  • Deep understanding of distributed systems and cloud-native application design.
  • Ability to balance reliability, security, scalability, and performance requirements.
  • Strong analytical and problem-solving skills.
  • Ability to lead technical initiatives and influence organizational technology adoption.
  • Strong collaboration and stakeholder engagement skills.
  • Excellent organizational skills and attention to detail.
  • Ability to mentor engineers and contribute to a culture of technical excellence.

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.