As an AI Engineer who thrives at the intersection of deeplearning research and productiongrade software development, you will translate cuttingedge AI concepts into robust, missionscale solutions for thewarfightingcommunity. You will work comfortably with largescale foundation models such as GPT andLLaMA, designing and deploying agentic workflows, as well as apply and advance traditionalMLresearch and engineering across domains such as naturallanguage processing, computer vision, timeseries 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 stringentmissionrequirements.

The Mission Innovation Lab within the SEIs AI Division works with the defense and national security community to translatethe2recentlypossible in AI into reliable mission and warfighting capabilities.

Key Responsibilities

• Design, develop,and finetune a variety of AI models.

• Design autonomous agents and multistep pipelines usingLangChain,ReAct, toolcalling, or custom orchestration; employ the ModelContext protocol to manage stateful interactions.

• Build RetrievalAugmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy forwarfightingapplications.

• Implement endtoend data pipelines, ETL processes, and backend 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;maintainmodel 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/LoRAmethods, and AIsafety techniques; translate new research into operational capabilities.

Required Qualifications

• Bachelors degree in Computer Science,Machine Learning, 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 andmaintainan active Department ofWar(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.

• Proficiencyin Python and at least one compiled language (C/C++ or Java); experience with REST/GraphQLAPIs and containerization.

• Strong grasp ofMLtheory (supervised, unsupervised, reinforcement learning) and evaluation metrics.

• Handson experience finetuning 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/LoRAmethods (e.g.,LoRA, adapters) to large models.

• Understanding of ModelContext protocols for managing model state across multiturn interactions.

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

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

• Awareness ofDevSecOpspractices (CI/CD,GitOps, container security scanning, modelregistry concepts) is desirable.

Desired Experience

• Deploying LLM APIs (FastAPI,gRPC) at scale, handlinglatencyand load balancing.

• Building multitool agents, plannerexecutor loops, or toolcalling pipelines for complex decisionmaking.

• Conducting adversarial testing, implementing input sanitization, and contributing to AIsafety research.

• Utilizing GPU/TPU resources, mixedprecision training, and distributed training frameworks such asDeepSpeedorZeRO.

• Prior work on defense, intelligence, or governmentfocused AI projects and familiarity withDoWacquisition or compliance processes.

• Contributing to opensource AIandMLlibraries, agentic frameworks, or contextprotocol implementations.

Knowledge, Skills, & Abilities

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

• Strong written and verbal communicationskillsfor documenting designs and presenting results to technical and nontechnical 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.