AI Engineer - Mission Innovation Lab

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.

As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we

• build real-world, mission-scale AI capabilities through solving practical engineering problems

• discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities

• prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities

• identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.

Overview

As an AI Engineer who thrives at the intersection of deep-learning research and production-grade software development, you will translate cutting-edge AI concepts into robust, mission-scale solutions for the warfighting community. You will work comfortably with large-scale foundation models such as GPT and LLaMA, designing and deploying agentic workflows, as well as apply and advance traditional ML research and engineering across domains such as natural language processing, computer vision, time series forecasting, and other predictive analytics. You will collaborate closely with senior researchers, software engineers, and government sponsors to define problem statements, iterate on experimental designs, and deliver secure, reliable AI capabilities that meet stringent mission requirements.

The Mission Innovation Lab within the SEI’s AI Division works with the defense and national security community to translate the “ recently possible” in AI into reliable mission and warfighting capabilities.

Key Responsibilities

• De sign, de velop, and fine - tune a variety of AI model s .

• Design autonomous agents and multi - step pipelines using LangChain, ReAct, tool - calling, or custom orchestration; employ the Model Context protocol to manage stateful interactions .

• Build Retrieval - Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications .

• Implement end - to - end data pipelines, ETL processes, and back - end services (Python, C/C++, Java) that feed data to models .

• Create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning; maintain model registries, monitoring, and version control of context protocols .

• Produce rapid prototypes, run benchmarks, and conduct robustness/adversarial testing in realistic environments.

• Work closely with senior ML engineers, software developers, and government customers; mentor junior staff and contribute to design reviews and documentation .

• Stay current with emerging LLM architectures, agentic paradigms, PEFT/ LoRA methods, and AI - safety techniques; translate new research into operational capabilities .

• Bachelor’s degree in Computer Science, Machine Learn ing, Statistics, Applied Mathematics, or a related field with at least eight (8) years of relevant experience, or a MS degree in the same with at least five (5) years of relevant experience.

• You will be subject to a background investigation and must be able to obtain and maintain an active Department of War ( DoW ) security clearance.

• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.

• Proficiency in Python and at least one compiled language (C/C++ or Java); experience with REST/ GraphQL APIs and containerization.

• Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics.

• Hands - on experience fine - tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools.

• Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers).

• Experience applying PEFT/ LoRA methods (e.g., LoRA, adapters) to large models.

• Understanding of Model Context protocols for managing model state across multi - turn interactions.

• Experience building evaluation frameworks, benchmarks, or data quality pipelines

• Experience with TensorFlow, PyTorch, or JAX; knowledge of data - pipeline tools (Airflow, Prefect, Ray) is a plus.

• Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model - registry concepts) is desirable.

Desired Experience

• Deploying LLM APIs ( FastAPI, gRPC ) at scale, handling latency and load balancing.

• Building multi - tool agents, planner - executor loops, or tool - calling pipelines for complex decision - making.

• Conducting adversarial testing, implementing input sanitization, and contributing to AI - safety research.

• Utilizing GPU/TPU resources, mixed - precision training, and distributed training frameworks such as DeepSpeed or ZeRO .

• Prior work on defense, intelligence, or government - focused AI projects and familiarity with DoW acquisition or compliance processes.

• Contributing to open - source AI and ML libraries, agentic frameworks, or context - protocol implementations.

Knowledge, Skills, & Abilities

• Analytical thinking: decompose complex AI problems into tractable components and iterate rapidly.

• Strong written and verbal communication skills for documenting designs and presenting results to technical and non - technical stakeholders.

• Proven teamwork: collaborate in interdisciplinary groups, mentor peers, and contribute to shared codebases.

• High curiosity and autonomy: proactively explore emerging technologies and integrate them into mission work.

Carnegie Mellon University challenges the curious and passionate to imagine and deliver work that matters.

A private, global research university, Carnegie Mellon stands among the world’s most renowned educational institutions, and sets its own course.

Carnegie Mellon was founded in 1900 by Andrew Carnegie under the premise that a school established to foster and develop the technical skills of its students would soon produce students and graduates whose work would astound Pittsburgh and the world. Over 120 years later, our institution continues to produce talented alumni and draws faculty and staff eager to be a part of the university’s creative, passionate and close-knit community. We place emphasis on practical problem solving, interdisciplinary learning, an entrepreneurial spirit, and collaboration.

Over the past 10 years, more than 400 startups linked to CMU have raised more than $7 billion in follow-on funding. Those investment numbers are especially high because of the sheer size of Pittsburgh’s growing autonomous vehicles cluster - including Uber, Aurora, Waymo and Motional - all of which are here because of their strong ties to CMU.

With cutting-edge brain science, path-breaking performances, innovative startups, driverless cars, big data, big ambitions, Nobel and Turing prizes, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we create it.

Pittsburgh is home to over 86,000 students from 10 colleges and universities. Pittsburgh was ranked as one of the top U.S. cities for millennials.

Some 177,000 people work in Pittsburgh’s tech-related industries, and their ranks continue to grow as the city tops lists for jobs. Networking opportunities, small business accelerators, and an innovative community make the city appealing to entrepreneurs, especially recent graduates.

Pittsburgh is emerging as a tech and culture hub that The Washington Post praises for its “world-class art museums and colorful neighborhoods.”

Robotics and software engineering lead the way. The city is home to Google, Uber and Apple offices and a budding ecosystem of tech startups including Duolingo, Modcloth and 4Moms, all of which have CMU roots.

Many seek Pittsburgh for being a hot spot for entrepreneurship and a model for future cities. Others come for the city’s burgeoning food scene.

You’ll find CMU locations nationwide - and worldwide. Silicon Valley. Qatar. Africa. Washington, D.C. To name a few., Carnegie Mellon University isn’t just one of the world’s most renowned educational institutions - it’s also a hotspot for some of the most talented doers, dreamers and difference-makers on the planet. When you join our staff, you’ll become an important part of our mission to create a healthier, safer and more just life for all. No matter what your role or location, you’ll connect and collaborate with dedicated, passionate colleagues - and you’ll have the satisfaction of delivering work that truly matters.

Carnegie Mellon University offers a wide range of competitive employee benefits to help you live well. Benefit eligibility varies based on the hours per week employees are scheduled to work and the employee’s geographic location

We seek to cultivate diverse populations and perspectives and promote equity and inclusion. Our devotion to these ideals springs from a core belief in the power of education to be a transformative and enriching force for every person, irrespective of their background, identity or life circumstances.

Inclusion and belonging are intricately interwoven into the very essence of our university, helping to shape our values, policies and practices. Diversity, equity, inclusion and belonging are not only central to our ethos but also indispensable to our pursuit of academic excellence and innovation.