Software Engineer - Applied AI/ML

Parsons; Maryland; On-site; USD 140,000 - 190,000; Full time

Job summary

Parsons is seeking an AI/ML Software Engineer to apply artificial intelligence and machine learning to cybersecurity challenges. You will develop full stack apps using LLMs and RAG, design AI/ML models, and integrate them into a secure cloud data platform.

You will work with data engineers and stakeholders to define requirements, validate outputs, and ensure compliance with cybersecurity and data privacy standards. Experience with Python, RESTful APIs, and cloud environments is essential.

Qualifications

• Develop AI/ML-enabled capabilities for data mining, predictive modeling, and knowledge discovery.
• Integrate AI/ML workflows into secure, cloud-based data architectures with standardized APIs.
• Collaborate with data engineers and stakeholders to define requirements, validate outputs, and support mission deliverables.

Responsibilities

• Develop full stack apps and services leveraging LLMs, RAG, agentic workflows and other AI capabilities.
• Design, deploy, and monitor AI/ML models and tools for data mining and predictive modeling.
• Ensure AI/ML workflows comply with DoW cybersecurity, data privacy, and access control, including isolated cloud environments.
• Assist knowledge transfer and training activities, including tutorials and best practices for AI/ML usage.

Skills

Python

REST APIs

Prompt engineering

ML concepts

LLMs & RAG

Cloud platforms

SQL

Containers

Security & compliance

Team collaboration

Education

Bachelor of Science in Computer Science, Cybersecurity, Information Systems, or related field

Tools

PowerShell

AWS / Azure

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next!

At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what's possible.

Job Description:

Parsons is looking for a talented AI/ML Software Engineer with a passion for applying artificial intelligence and machine learning to real-world cybersecurity challenges to join our growing team!

What You'll Be Doing :

• Develop full stack applications and services that leverage large language models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and other emerging AI capabilities.
• Designing, developing, and deploying AI/ML models and tools for data mining, predictive modeling, and knowledge discovery
• Integrate AI/ML-enabled capabilities into a secure, cloud-based data architecture, ensuring interoperability with existing systems via standardized APIs
• Implement and monitor model performance, data/concept drift, and key metrics in real time; support model retraining and fine-tuning as new data becomes available
• Collaborate with data engineers, software developers, and stakeholders to define requirements, validate outputs, and support mission deliverables
• Ensure all AI/ML workflows comply with DoW cybersecurity, data privacy, and access control requirements, including operation within isolated cloud environments.
• Assist in knowledge transfer and training activities, including the development of tutorials and best practices for AI/ML usage.
• Educate stakeholders on AI platform concepts, emerging patterns, and implementation best practices in government environments.
• Assessing data patterns in systems and network misconfiguration.
• Working with a team of Cyber Analysts to support quick turn requests for vulnerability information by continually improving LLMs
• Conduct analyses of alternatives (AoAs) to compare internally developed approaches against commercial, open-source, and industry-standard techniques.
• Develop and execute experiments to assess model performance using appropriate evaluation metrics and representative datasets.

What Required Skills You'll Bring :

• Active TS/SCI with Poly required
• Bachelor of Science in Computer Science, Cybersecurity, Information Systems, or related field and 10+ years of relevant experience. With additional years of experience able to count in lieu of a degree, and vice versa.
• Familiarity with machine learning concepts, including model training, evaluation, tuning, and performance measurement.
• Ability to assess model effectiveness using quantitative metrics and communicate tradeoffs.
• Depth of experience with prompt engineering.
• Proficiency in Python and experience developing RESTful APIs and backend services.
• Experience supporting AI/ML, data, cloud, or platform engineering efforts in government, defense, or enterprise environments.
• Understanding of modern AI concepts, including LLMs, embeddings, RAG, vector search, and agentic workflows.
• Demonstrated familiarity with Microsoft and/or AWS platform ecosystems
• Proficiency using command-line interfaces such as Windows PowerShell/Command Prompt for routine development, troubleshooting, scripting, and automation tasks
• Working knowledge of cloud architecture, containers, APIs, data services, identity/access management, and secure system integration.
• Ability to understand how AI applications depend on underlying platform components such as model hosting, pipelines, storage, orchestration, and monitoring.
• Demonstrated experience in database management, including designing and maintaining relational databases, writing and optimizing SQL queries, implementing backup and recovery procedures, and applying database security and performance best practices.
• Demonstrated experience with configuration management, including defining and maintaining configuration baselines, using configuration management tools e.g.,Ansible, Puppet, Chef, Terraform to manage infrastructure and application settings
• Passionate about AI and platform modernization.
• Ability to rapidly prototype solutions, iterate based on user feedback, and operate effectively in ambiguous problem spaces.
• Able to translate complex technical issues into actionable guidance for mixed technical and non-technical audiences.
• Mission-oriented, collaborative, and proactiv