Senior AI Software Engineer (Cloud-Native)

Comcast Resume; Reston (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

FreeWheel, a Comcast company, seeks a software engineer to develop AI-enabled product capabilities and own AI-powered features with product and engineering collaboration to deliver scalable, reliable solutions.

You will design and deploy cloud-native apps, integrating LLMs, agents, and automation, while driving observability, performance, and quality across deployments. Mentoring and architectural input are also expected.

Qualifications

• 3+ years of software engineering experience.
• Strong programming skills in Python.
• Experience building and deploying cloud-native applications.
• Experience working with AI/ML platforms, LLMs, agents, or intelligent automation solutions.
• Understanding of APIs, distributed systems, and software architecture patterns.
• Experience delivering production software in collaborative engineering environments

Responsibilities

• Designing and implementing AI-powered product features and services.
• Developing applications and workflows that integrate LLM, agent, or machine learning capabilities.
• Contributing to evaluation, observability, and continuous improvement of AI solutions.
• Collaborating with product, data, and engineering teams to translate requirements into technical solutions.
• Improving reliability, performance, and scalability of AI-powered capabilities.
• Participating in architecture discussions and technical design reviews.
• Troubleshooting production issues and driving root-cause analysis.
• Contributing reusable components and patterns that accelerate AI adoption across teams.

Skills

AI Agents

Software Development

Software Testing

Education

Bachelor's Degree

Job description

FreeWheel, a Comcast company, seeks a software engineer to develop AI-enabled product capabilities and own AI-powered features with product and engineering collaboration to deliver scalable, reliable solutions.

You will design and deploy cloud-native apps, integrating LLMs, agents, and automation, while driving observability, performance, and quality across deployments. Mentoring and architectural input are also expected.