Welcome to my personal website!
Mohammad Jalili
I’m a Software Engineer with an M.S. in Computer Science, focused on scalable APIs, data pipelines, and applied machine learning.
My work spans backend engineering, LLM-powered automation, and software security systems — with an emphasis on reliability, testing, and real-world impact.
Mohammad Jalili
contact@mjalili.com
Time Zone
Central Standard Time (CST)
Education
M.S. in Computer Science
2024 – 2025
University of Nebraska-Lincoln | United States
B.S. in Computer Engineering
2016 – 2020
KNTU University of Technology | Iran
Experience
Software Engineer, University of Nebraska-Lincoln (UNL)
January 2024 – Present
• Developed Python and Java services for automated classification of software vulnerabilities, processing hundreds of
CVE/CWE records daily.
• Built and maintained robust data pipelines for CVE, CWE, and CVSS datasets, enabling reliable model reasoning
over large-scale security data.
• Implemented automated testing and evaluation workflows, improving vulnerability classification accuracy and
consistency by 20%.
• Integrated LLM-based models into production-style workflows with prompt engineering and fine-tuning, balancing
latency, cost, and performance.
• Collaborated with research and engineering teams to bridge ML research and real-world security applications.
Software Engineer – Web Platform, Arzyaban Salamat Pars Co.
April 2022 – July 2022
• Designed and developed production-ready backend services, data models, and APIs for internal web applications
supporting operational workflows.
• Implemented database schemas and backend logic using ASP.NET and relational databases, improving data
reliability and query performance.
• Contributed to deployment and release workflows, increasing system stability and maintainability.
• Collaborated with cross-functional teams to deliver features on schedule in a fast-paced environment.
Software Engineer – Mobile Platform, Ertegha Salamat Pasargad Co.
Jul 2020 – Aug 2020
• Developed two Android applications for internal staff and partner centers, implementing core features in Java.
• Streamlined operational workflows for insurance services, improving internal efficiency.
Software Engineer – Mobile Platform, Ayandeh Sazan Publications.
Oct 2018 – May 2020
• Built and maintained an Android app delivering personalized study plans for high school students.
• Integrated data-driven adaptive logic to tailor study schedules based on user behavior and inputs.
• Focused on usability, performance, and maintainability to support 10,000+ active users.
Founding Software Engineer, SeedS/Lexeen Startup.
Oct 2016 – Oct 2019
• Developed applied software engineering programs covering neural network fundamentals and Android app
development.
• Mentored small teams to deliver Java-based Android applications in real-world use cases.
• Built production-ready apps and programs emphasizing practical implementation.
Software Engineer Intern, Sarmad Insurance.
Jul 2019 – Sep 2019
• Developed an Android app to calculate insurance premiums by implementing the company’s business rules.
• Collaborated with domain experts to ensure accurate and maintainable application logic.
Main Skills
Primary Skills and Areas of Expertise
01
Software Engineering
I am a backend-focused software engineer with experience designing and building scalable, production-grade systemswith an emphasis on asynchronous processing, distributed architectures, and AI-powered services. My work centers on developing reliable REST APIs, background task pipelines, and backend services using Python and Java, following clean architecture principles and modular design for long-term maintainability.
I have hands-on experience building containerized, multi-service systems using FastAPI, MongoDB, Redis, and Docker, including JWT-secured APIs, asynchronous database access, and distributed task queues for handling long-running and compute-intensive workloads. I have designed backend systems where AI and LLM-based components are integrated as first-class services, enabling scalable inference, automated analysis, and decoupled processing via background workers.
I place a strong emphasis on software quality and reliability, applying engineering best practices such as unit testing, test-driven development, automated evaluation, and systematic debugging. Across academic and industry environments, I have collaborated with cross-functional teams to translate requirements into robust system designs, deliver features on schedule, and maintain production services that balance performance, scalability, and long-term maintainability.
02
AI/LLM
My work in AI focuses on applied machine learning and the production integration of large language models into real-world software systems. I have designed and implemented end-to-end ML pipelines spanning data ingestion, feature engineering, model training, evaluation, and deployment, with hands-on experience in security-focused applicationssuch as vulnerability classification and assessment. Rather than treating models as isolated components, I integrate them into backend-driven workflows where accuracy, latency, scalability, and cost must be carefully balanced.
I have substantial practical experience working with large language models, including prompt engineering, few-shot learning, fine-tuning, and retrieval-augmented generation (RAG). I have built modular and reusable LLM pipelinesusing tools such as LangChain, supporting tasks including code analysis, automated testing, ticket classification, and report generation. My approach emphasizes measurable outcomes, reproducibility, and operational reliability, ensuring that LLM-based systems remain interpretable, maintainable, and suitable for deployment beyond experimental or research-only settings.
Places I’ve Worked
Contact Me
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