Developer Jobs in Los Alamos, NM

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1mo ago

Applied AI Software Developer (Software Developer 2/3)

Los Alamos National Laboratory Los Alamos, NM

Los Alamos, NM

1mo ago Closed

$88k - $172k/yr Full time Python Artificial Intelligence DevOps

This position is no longer accepting applications (closed Jul 4, 2026).

Job Description

Los Alamos National Laboratory is seeking an Applied AI Software Developer (Software Developer 2/3) to help design and deploy AI-enabled software solutions for assurance and cyber-physical resilience within the Nuclear Weapons Cyber Assurance Laboratory (NWCAL). This role sits at the crossroads of software engineering and advanced AI, addressing mission-critical challenges in hardware/software assurance and operational resilience through scalable, production-ready applications.

Location

Los Alamos, NM (onsite)

Salary

USD 87,800 - 172,200 per yearly

Requirements

Bachelor's degree in a relevant technical field and 5 years related experience; or, an equivalent combination of education and experience directly related to the occupation.
Bachelor's degree in a relevant technical field and 8 years related experience; or, an equivalent combination of education and experience directly related to the occupation.
Active DOE Q Clearance
Ability to obtain a DOE Q-clearance is required
Knowledge and experience programming in Python with modern AI/ML frameworks and libraries such as PyTorch, TensorFlow, Pandas, NumPy, SciPy, or similar technologies
Knowledge and experience developing and deploying AI-enabled applications utilizing technologies such as large language models (LLMs), retrieval augmented generation (RAG), agentic workflows, model orchestration frameworks, or related AI technologies
Knowledge and experience developing software within Linux environments using modern software development tools and workflows including Git, GitLab, containerization technologies, and CI/CD pipelines
Knowledge and experience developing applications utilizing GPU-enabled local and distributed compute environments
Knowledge and experience working within collaborative software development environments utilizing modern development standards and engineering best practices
Ability to work effectively within multidisciplinary technical teams consisting of software developers, engineers, analysts, and scientific staff
Ability to communicate technical concepts and development activities to both technical and non-technical stakeholders

Responsibilities

Collaborate as part of a multidisciplinary engineering team to design, implement, and maintain AI-enabled software applications and workflows that support assurance and operational mission objectives
Develop AI-enabled applications using modern machine learning and large language model technologies
Build scalable software systems for local and distributed compute environments
Integrate AI capabilities into operational workflows
Contribute to software development activities across the application lifecycle including implementation, testing, deployment, and sustainment
Develop within Linux-based environments using modern development tools, containerized workflows, source control systems, and CI/CD practices
Address technically challenging mission problems involving AI systems, cyber-physical environments, and operational assurance capabilities
Demonstrate advanced technical capability in the development and implementation of applied AI software systems and modern software engineering practices
Contribute to the design, implementation, and deployment of purpose-built AI-enabled applications operating in production or operational environments
Take on independent technical contributions to software architecture, AI workflow implementation, development standards, and engineering execution across collaborative teams
Apply formal software development lifecycle practices including source control, testing methodologies, deployment workflows, and maintainable software design principles
Provide technical direction, mentorship for less experienced developers, and guidance on implementation approaches for mission-focused AI capabilities

Technologies

Python
PyTorch
TensorFlow
Pandas
NumPy
SciPy
Large language models (LLMs)
Retrieval augmented generation (RAG)
Agentic workflows
Model orchestration frameworks
Linux
Git
GitLab
Containerization technologies
CI/CD pipelines
GPU-enabled compute environments
Kubernetes
OpenShift
Distributed computing platforms
Scalable AI infrastructure technologies

Benefits

Health insurance (PPO or High Deductible)
Dental and vision insurance
Life and disability insurance
Paid childbirth and parental leave
401(k) with matching
Tuition assistance
Flexible schedules and paid time off
Onsite gyms and wellness programs
Relocation assistance/packages

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