AI Engineer

Overview

At Leidos, you ll contribute to AI solutions that serve critical national and global missions—ranging from defense and intelligence to healthcare, energy, and space exploration. Our work emphasizes Trusted Mission AI: systems that are transparent, ethical, resilient, and accountable. You ll collaborate with multidisciplinary teams to transition AI research into operational environments where accuracy, security, and reliability are non-negotiable. Joining Leidos means applying your expertise to solve some of the most complex and meaningful challenges of our time.

We are looking for a motivated AI engineer who wants to work on challenging problems in a variety of domains – including enterprise IT, health, defense, intelligence, and energy – to get results that apply and go beyond the state of the art for measurably better outcomes. We apply our knowledge, capabilities, and experience to develop and deploy Trusted Mission AI – AI that deserves to be trusted by system owners, end users, and the public – to be helpful, harmless, and honest.

We are looking for a researcher that is expert in envisioning, developing, and securing AI agents using generative AI and LLM-based tools to transform and add value to human workflows.

• The AI Engineer will collaborate closely with Agentic AI Scientists and product teams to design, build, and deploy agentic AI systems that automate and optimize labor-intensive workflows while enabling the human workforce with new, AI-powered capabilities.
• As a member of the Leidos AI Accelerator, this role will span both research and development and customer-facing delivery, accelerating the transition of applied research and prototype solutions into operational impact on contract.
• The AI Engineer will be responsible for developing and maintaining full-stack software that supports agentic AI workflows. This includes building user-facing interfaces and tools, implementing backend services and APIs, and writing application logic that enables agent communication, orchestration, and tool use.
• The role will involve integrating AI models and agents with external systems and services via APIs, supporting testing and debugging, deploying solutions into target environments, configuring monitoring and logging, and ensuring reliable, secure execution of agentic AI systems in production.
• The engineer will work with a mix of open-source models, agentic frameworks, and proprietary commercial AI services. They will contribute to the development of approaches for securing agentic workflows and for evaluating system behavior with respect to accuracy, performance, reliability, and mission impact. They will also help ensure that AI systems adhere to ethical guidelines and principles of transparency, accountability, and fairness.
• Depending on project needs, the Agentic AI Engineer may conduct applied research, develop prototypes, and evaluate and document results, including contributing to technical reports, publications, or conference presentations. They may also be part of teams delivering solutions for deployment into operational environments or integrating AI capabilities into existing mission systems.
• This role requires a self-motivated engineer who can take ownership of complex features while collaborating effectively within a multidisciplinary team. The engineer is expected to actively share discoveries, seek feedback, and contribute to a culture of continuous learning and innovation across the AI Accelerator.

• Bachelor’s degree in Computer Science, Engineering, or a related field with 2+ years of relevant professional experience, or a Master’s degree with relevant experience.
• Strong software engineering fundamentals with hands-on experience building production systems.
• Proficiency in modern programming languages, including Type Script/JavaScript for application development and Python for AI integration and prototyping.
• Experience building full-stack applications, including frontend development (React) and backend services/APIs (Node.js / python).
• Practical understanding of large language models (LLMs) and experience using agent frameworks such…