Lead AI/ML Engineer

FTI - Frontier Technology Inc.

Distinguished AI/ML Engineering Lead integrating AI systems for mission success in secure environments. FTI Defense seeking a hands-on builder in high-stakes engineering solutions.

Posted 6/12/2026full-timeRemote • Colorado • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AirflowDockerKafkaKubernetesMicroservicesPythonPyTorchSparkTensorflowTypeScript

About the role

Key responsibilities & impact

Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
Lead the full AI/ML lifecycle — from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems.
Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.

Requirements

What you’ll need

Active Secret clearance required; TS/SCI strongly preferred.
Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s or Ph.D. preferred).
10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

Benefits

Comp & perks

Telecommute
Health benefits

ATS Keywords

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Hard Skills & Tools

machine learningdeep learninglarge language modelsretrieval-augmented generationdata ingestionfeature engineeringMLOpsevent-driven data pipelinesmodel qualityethical AI deployment

Soft Skills

technical leadershipmentorshipcommunicationcollaboration

Certifications

Active Secret clearanceTS/SCI