Senior Applied AI Infrastructure Engineer - NREC
Carnegie Mellon University
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Benefits offered by this job
Job summary
National Robotics Engineering Center (NREC) at Carnegie Mellon University in Pittsburgh seeks a Senior Applied AI Infrastructure Engineer to lead the evaluation, deployment, and integration of secure generative AI tools and LLMs across engineering workflows. You will help design, host, and optimize AI services on secure, multi-GPU infrastructure.
You will collaborate with leadership and multidisciplinary teams to advance AI-assisted workflows, ensure reliability, and push the boundaries of
Qualifications
- B.S. in Computer Science, Computer Engineering, Electrical Engineering, or related field or equivalent experience.
- 5+ years of professional software engineering, machine-learning infrastructure, DevOps, platform engineering, or developer-tools experience.
- Strong Python programming skills.
- Linux development and system-administration experience.
- Familiarity with large language models, retrieval-augmented generation, tool-using agents, or AI-assisted software-development workflows.
- Strong technical communication and documentation skills.
- 3+ of the following: experience deploying and maintaining software services; Docker and container experience; API integrations; modern software engineering practices (Git, code review, CI/CD, testing, logging, debugging); ability to evaluate new technologies and communicate tradeoffs.
Responsibilities
- Evaluate generative and agentic AI tools and recommend practical approaches to engineering leadership.
- Support cloud-hosted AI tools where appropriate and locally hosted tools where confidentiality requires it.
- Design, implement, document, test, and maintain internally hosted AI services and supporting infrastructure.
- Deploy and operate large language models on shared GPUs and project-specific platforms.
- Integrate AI tools with engineering systems (source control, Jira, Confluence, Jenkins, internal docs, test infra).
- Develop secure tool interfaces, Model Context Protocol servers, and sandboxed environments for AI agents.
- Prototype and evaluate AI-assisted workflows for software development, testing, docs, and analysis.
- Help engineers use supported AI tools across software, embedded, FPGA, mechanical, electrical workflows.
- Create internal docs, examples, training materials, and reusable configurations for tools and practices.
- Measure reliability and usefulness of AI-assisted workflows (code quality, tests, reviews, failure modes).
- Survey emerging tools and implement promising approaches where valuable.
- Follow best practices for team software development (peer review, automated testing, version control, issue tracking, security review, docs).
Skills
Education
Tools
Job description
At the National Robotics Engineering Center (NREC), it is ourengineers and technicians who drive the breakthroughs that defineour success. The members of our technical staff collaborate closelywith leadership and multidisciplinary teams to design, build, anddeploy sophisticated robotic solutions that address complexchallenges in industrial, commercial and government sectors. Eachproject benefits from their expertise, creativity, and hands‑onproblem‑solving, fueling progress and innovation across theorganization.
As part of our dedicated team, you will work alongside world‑classrobotics professionals committed to pushing the boundaries oftechnology and redefining ideas into solutions for real‑worldapplications. We foster a culture of professionalism, respect, andcollaboration, offering a flexible and encouraging environmentwhere you can sharpen your skills, lead impactful projects, andtake control of your career development.
We are seeking a dynamic Senior Applied AI Infrastructure Engineerto lead and contribute to the evaluation, deployment, andintegration of secure generative and agentic AI tools, LLMs, andsupport of self‑hosted infrastructure across engineering workflows.This is an exciting opportunity for someone who thrives in a fast‑paced and innovative setting. In this role, you will beinstrumental in advancing internal AI-assisted workflows,infrastructure reliability, and secure multi‑GPU model serving,ensuring our team delivers exceptional and groundbreakingresults.
- Evaluating generative and agentic AI tools and recommendingpractical approaches to engineering leadership.
- Supporting cloud‑hosted AI tools where appropriate and locallyhosted tools where project confidentiality or data‑handlingrequirements prohibit cloud use.
- Designing, implementing, documenting, testing, and maintaininginternally hosted AI services and supporting infrastructure.
- Deploying and operating large language models on shared GPUsystems and smaller project‑or team‑specific platforms.
- Integrating AI tools with engineering systems such assource‑code repositories, Jira, Confluence, Jenkins, internaldocumentation, and test infrastructure.
- Developing secure tool interfaces, APIs, Model Context Protocolservers, and sandboxed environments that allow AI agents to performuseful engineering tasks.
- Prototyping and evaluating AI‑assisted workflows for softwaredevelopment, testing, documentation, requirements analysis, andother engineering activities.
- Helping engineers use supported AI tools effectively acrosssoftware, embedded, FPGA, mechanical, electrical, and othertechnical workflows.
- Developing internal documentation, examples, trainingmaterials, and reusable configurations for recommended tools andpractices.
- Measuring the reliability and usefulness of AI‑assistedworkflows, including the quality of generated code, test results,review effort, and failure modes.
- Surveying emerging tools and techniques and implementingpromising approaches where they provide practical value.
- Following best practices for team software development,including peer review, automated testing, version control, issuetracking, security review, and integrated documentation.
- B.S. in Computer Science, Computer Engineering, ElectricalEngineering, or a related technical discipline, or equivalentexperience.
- 5+ years of professional software engineering, machine‑learninginfrastructure, DevOps, platform engineering, or developer‑tools experience.
- Strong Python programming skills.
- Linux development and system‑administration experience.
- Familiarity with large language models, retrieval‑augmentedgeneration, tool‑using agents, or AI‑assisted software‑developmentworkflows.
- Strong technical communication and documentation skills.
- 3 or more of the following:
- Experience deploying and maintaining software services.
- Experience with containers and reproducible deployment toolssuch as Docker.
- Experience integrating software systems through APIs,command‑line tools, authentication mechanisms, or similarinterfaces.
- Experience with modern software engineering practices,including version control, code review, testing, CI/CD, logging,and troubleshooting.
- Ability to evaluate new technologies, communicate technicaltradeoffs, and make practical recommendations.
- Self‑hosted LLM inference frameworks such as vLLM,TensorRT‑LLM, llama.cpp, Ollama, NVIDIA NIM, or similar tools
- Multi‑GPU systems, model serving, resource scheduling, orinference performance optimization
- Model Context Protocol servers or other structured interfacesfor AI tool use
- Integration with Jira, Confluence, Jenkins, Git‑basedrepositories, artifact repositories, or internal knowledgesystems
- Coding agents that can modify code, run builds and tests, andprepare pull requests
- Sandboxed code execution, container isolation, secretsmanagement, access control, or audit logging
- Evaluation of LLM applications, coding assistants, agents, orretrieval systems
- Retrieval‑augmented generation, document ingestion, embeddings,reranking, or code indexing
- Cloud AI services and data‑sensitive or disconnected AIdeployments
- Embedded software, FPGA development, robotics, simulation, orhardware‑in‑the‑loop testing
- GPU‑based machine learning infrastructure
- Developing internal technical documentation, training,examples, or reusable engineering workflows
- Machine learning, computer vision, or roboticsapplications
- Successful pre‑employment background check
This position will require work on a variety of projects,including projects that involve military/defense applicationsand/or are funded by military/defense sponsors.
Are you interested in joining our versatile team at NREC where youwill have a direct impact on operations and meaningfulprojects?
Join a collaborative environment where your hands‑on skills,leadership, and mentorship will directly influence operations andinspire the next generation of innovators.
At NREC, you will shape the robotics revolution by tacklingreal‑world challenges in agriculture, manufacturing, defense,energy, and much more. You will work alongside top roboticsexperts, develop ground breaking technologies, and see your solutions deployed in the field.
- Located in Pittsburgh or "Roboburgh", a hub for over 120+robotics companies
- 30+ years of pioneering robotics research
- 150+ professionals driving innovation and real‑worldimpact
- Part of Carnegie Mellon's Robotics Institute,a global leader in robotics
NREC also leads in educational outreach through its RoboticsAcademy, which develops curricula and software for K-12 andcollege-level students. You will also have opportunities to engagewith these student groups through outreach activities.
As part of our team, you will have the flexibility to grow yourcareer - whether becoming a technical expert, leading projects,mentoring others, or exploring new pathways and making an impact indeveloping technologies that drive progress, improve safety andtransform industries.
Joining the CMU team opens the door to an array of exceptionalbenefits.
Benefits eligible employees enjoy a wide array ofbenefits including comprehensive medical, prescription, dental, andvision insurance as well as a generous retirement savings program with employercontributions. Unlock your potential with tuition benefits, take well‑deserved breaks withample paid time off and observed holidays, and rest easy with life and accidentaldeath and disability insurance.
Additional perks include a free Pittsburgh Regional Transit buspass, access to our Family Concierge Team to help navigatechildcare needs, fitness center access, and much more!
For a comprehensive overview of the benefits available, exploreour Benefits page.
At Carnegie Mellon, we value the whole package when extendingoffers of employment. Beyond credentials, we evaluate the role andresponsibilities, your valuable work experience, and the knowledgegained through education and training. We appreciate your uniqueskills and the perspective you bring. Your journey with us is aboutmore than just a job; it's about finding the perfect fit for yourprofessional growth and personal aspirations.
Are you interested in an exciting opportunity with anexceptional organization?! Apply today!
Pittsburgh, PA
Software/Applications Development/Engineering
Staff – Regular
Full time
Salary
- Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that changethe world.
- Click here to view a listing of employee benefits
- Carnegie Mellon University is an Equal OpportunityEmployer/Disability/Veteran.
- Statement of Assurance
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