DevOps/AI Engineer

The MITRE Corporation•McLean, VA

2d•$95,200 - $142,800•Onsite

About The Position

At MITRE, your passion fuels work that impacts our nation and improves lives. This is where your skills strengthen national security, cybersecurity, health, transportation, and citizen services. We’re a nonprofit engineering, applied research, and advanced technology organization working in the public interest. With objectivity and integrity at our core, we lead federally funded research and development centers for U.S. government agencies – collaborating with industry and academia to deliver integrated, high-impact solutions that advance our nation’s health, security, and prosperity. Our people tackle the toughest technical challenges, supported by competitive benefits, meaningful career development, and a culture of innovation, collaboration, and technical excellence. Choose MITRE for a career with purpose — and help shape the future. Digital Engineering & Systems Transformation is aimed at leveraging advanced technologies and enablers to drive engineering innovation, speed, and efficiency. This role is aligned to the Digital Engineering & Systems Transformation department. MITRE is seeking a Senior Multidiscipline Engineer with emphasis on DevOps and AI to join a dynamic and multi-disciplined organization involved in innovating solutions for complex technical systems. MITRE seeks professionals with various expertise (e.g., software tools, processes, DevSecOps, CI/CD, MLOps, AI-enabled systems, cloud services, agile methodologies, transition design, etc.) to work with a team of experienced experts driving digital transformation efforts.

Requirements

Bachelor’s degree in computer science, Computer Engineering, Systems Engineering, or a related technical discipline (e.g., Electrical Engineering, Data Science, or Applied Mathematics) and a minimum of 2 years of related experience; or a master’s degree and 1 years of related experience; or a PhD with relevant experience; or an equivalent combination of related education and work experience
Demonstrated, hands-on experience across the software development lifecycle using modern programming languages such as Python, Java, or C++
Proven experience designing and implementing DevOps practices, including automation, testing, CI/CD pipelines, and containerization (e.g., Docker, Kubernetes, GitHub Actions, or Jenkins)
Working knowledge of cloud platforms (e.g., AWS, Azure, or GCP) and how they support scalable, distributed systems
Experience applying Agile or Scrum methodologies and collaborative software development practices
Strong analytical, communication, and teamwork skills, with a demonstrated ability to learn and apply new tools and technologies
This position requires a minimum of 4 days a week on-site

Nice To Haves

3+ years of experience applying DevOps, MLOps, or AI/ML techniques to real-world or operational systems
Experience with cloud-native technologies and infrastructure as code (e.g., AWS, Azure, GCP, or Terraform), including provisioning IaaS/SaaS and automating deployments to enhance operational efficiency
Hands-on experience with large language models (LLMs) and emerging AI tools (e.g., OpenAI, Hugging Face, LangChain), with interest in applying them to engineering workflows or digital transformation efforts
Proficiency across a broad software stack including Java, Python, SQL, JavaScript, XML, JSON, HTML/CSS, Shell, MySQL, MongoDB, and Git
Experience developing or deploying applications using modern frameworks, APIs, or microservices architectures
Exposure to modeling and simulation for systems design, digital twins, or model-based systems engineering (MBSE)
Knowledge of data management principles, database design, and approaches for working with structured and unstructured data
Active or current DoD or federal government security clearance

Responsibilities

Leading the design, prototyping, and delivery of DevOps and AI/ML capabilities that advance systems engineering practices and improve sponsor outcomes.
Architecting and implementing CI/CD pipelines, containerized deployments, and MLOps workflows across cloud and on-premises environments to accelerate speed of delivery.
Applying AI and ML (including LLMs) and emerging technologies to improve engineering methodology and automate complex workflows.
Increasing the use of modeling throughout the SELC, advancing the implementation of Systems of Systems and improving system interoperability and data management.
Developing reusable artifacts, reference architectures, and prototypes, and promoting their adoption across teams.
Modernizing legacy IT infrastructure by implementing secure, scalable, and efficient solutions and accelerating adoption of cloud and emerging technologies.
Providing technical guidance and mentorship to junior engineers while collaborating across multi-disciplinary teams.