Senior AIML Engineer

General program information and/or position overview.

This Department of War enterprise data and analytics program delivers mission-critical capabilities that enable leaders across the Department to make faster better-informed decisions using trusted data at scale. Leidos Digital Modernization sector is seeking an experienced Senior AI/ML Engineer to support the delivery enhancement and adoption of enterprise data and analytics products used across multiple DoD this role you will work alongside government partners engineers and other industry teammates to translate operational and strategic requirements into scalable production-ready solutions. You will contribute directly to product planning execution and continuous improvementhelping ensure capabilities are delivered efficiently aligned to mission priorities and positioned for sustained position offers the opportunity to work on a high-visibility enterprise program at the intersection of data analytics and emerging AI technologies. Ideal candidates are motivated by mission impact comfortable operating in complex stakeholder environments and interested in building deep domain expertise while delivering capabilities with real-world national security outcomes.

Primary Responsibilities:

• Design develop and optimize AI and ML solutions to enhance operational and analytical capabilities within a larger enterprise level Data and AI analytics platform.

• Build and maintain end-to-end ML pipelines including data ingestion feature engineering model training validation and inference.

• Train and tune algorithms to improve predictive accuracy and decision-support tasks.

• Integrate AI/ML models into production environments using APIs microservices and DevSecOps pipelines.

• Support development and maintenance of model serving infrastructure and scalable inference capabilities.

• Implement model monitoring performance evaluation and drift detection mechanisms.

• Optimize model performance scalability and efficiency for production workloads.

• Collaborate with data engineers data scientists software developers and DevSecOps teams to ensure alignment with enterprise architecture and security requirements.

• Support secure development and deployment of AI/ML models in compliance with enterprise cybersecurity requirements.

• Contribute to development of AI/ML artifacts including documentation testing frameworks and model evaluation reports.

• Support integration with enterprise AI/ML platforms and external model providers (e.g. cloud-based AI services).

• Ensure compliance with cybersecurity policies and standards throughout the project lifecycle.

• Stay updated on industry trends and advancements in AI/ML technologies.

• Identify and resolve technical challenges related to model accuracy scalability and integration.

• Analyze system performance metrics and recommend improvements for efficiency and scalability.

• Identify and integrate appropriate COTS government and custom tools within established frameworks.

• Manage project timelines and deliverables ensuring adherence to quality standards.

• Facilitate communication between technical teams and stakeholders to align project goals.

• Develop and implement best practices for model development and deployment.

Basic Qualifications:

• Active Secret clearance.

• Bachelors degree in Computer Science Data Science Artificial Intelligence Engineering or related technical discipline and 812 years of relevant experience OR Masters degree in a related field and 610 years of relevant experience.

• Minimum of 6 years of experience in AI/ML and/or data intelligence engineering or related fields.

• Experience developing and deploying machine learning models in enterprise environments.

• Experience with programming languages such as Python R or Java and ML frameworks such as PyTorch TensorFlow or Scikit-learn.

• Experience building and maintaining ML pipelines and data processing workflows.

• Experience deploying models in containerized environments (Docker Kubernetes).

• Experience integrating AI/ML solutions into APIs and microservices architectures.

• Experience implementing model evaluation performance tuning and lifecycle management practices.

• Experience with data pipeline construction and management.

• Strong problem-solving abilities and analytical thinking.

• Strong communication and interpersonal skills.

• Experience in at least 2 of the following:

• Developing Agentic AI solutions including autonomous planningexecutionreflection loops multi-agent collaboration and coordination and tool usage patterns including API integration retrieval-augmented generation (RAG) and memory/context management

• Generative AI models including prompt engineering chain-of-thought reasoning and Natural Language Processing (NLP) tasks such as entity extraction summarization and semantic search.

• Large Language Models (LLMs) and agent frameworks such as LangChain LangGraph CrewAI A2A MCP or AutoGen

• Vector databases (e.g. Pinecone Weaviate FAISS)

• Deployment into virtualized and containerized environments (e.g. VMware Docker Kubernetes)

Preferred Qualifications:

• Active Top Secret clearance.

• 10 years of experience in AI/ML and/or data intelligence engineering or related fields.

• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.

• Experience supporting AI/ML solutions across multi-enclave DoD environments.

• Experience integrating AI/ML models into CI/CD and DevSecOps environments.

• Experience developing and deploying AI/ML models using frameworks such as PyTorch TensorFlow or equivalent.

• Experience working with vector databases and retrieval-augmented generation (RAG) architectures.

• Experience with cloud-based AI/ML platforms (AWS Azure or GCP).

• Experience implementing automated model validation bias detection and drift monitoring frameworks.

• Experience integrating AI services into enterprise APIs and microservices architectures.

• Experience optimizing GPU-based training and inference pipelines.

• Experience supporting enterprise-scale analytics data platforms or AI modernization initiatives.

• Experience with cloud-based AI/ML platforms and tools.

• Familiarity with cybersecurity principles and practices.

• Experience designing and implementing safety guardrails and bias-mitigation strategies for autonomous agents and multiagent systems

• Experience integrating agents with cloud-native workflows streaming data pipelines and real-time decision-making environments

• Familiarity with evaluation and observability tools for AI agents such as LangSmith OpenAI Evals or custom telemetry systems

• Experience with AI service integration such as NIMS Azure OpenAI Bedrock GCP Vertex AI

• Hands-on GPU programming experience for ML workloads using CUDA PyTorch or TensorFlow including optimization for performance and efficiency.

If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job education experience knowledge skills and abilities as well as internal equity alignment with market data applicable bargaining agreement (if any) or other law.