Sr. Applied AI Engineer

Salary: $98,678.8 - 231,278.44 per year Requirements:

• We require strong expertise in Python and experience building microservices that include advanced analytical logic.
• We value demonstrated experience working with cybersecurity datasets and applying machine learning to support security compliance and threat hunting.
• We look for hands-on experience parsing, cleansing, and normalizing data, with a strong preference for using machine learning to improve those processes.
• We need experience designing, developing, and deploying applications powered by large language models, including conversational AI, chatbots, and AI assistants.
• We expect experience with retrieval-augmented generation, semantic search, vector databases, embeddings, and prompt engineering.
• We require experience integrating foundation models such as OpenAI, Anthropic, Gemini, or open-source LLMs into production systems through APIs and orchestration frameworks.
• We value experience evaluating, fine-tuning, and optimizing LLM-based solutions, including model selection, prompt tuning, guardrails, and performance assessment.
• We look for understanding of AI governance, responsible AI practices, model monitoring, and security considerations for generative AI applications.
• We require experience building scalable AI and machine learning pipelines and deploying models using MLOps best practices.
• We expect experience working in Agile Scrum environments.
• We require experience using GitHub, Jira, or similar collaboration tools.
• We look for experience using Python unit test frameworks.
• We require experience with Docker and containerized application deployment.
• We value experience developing SaaS products.
• Experience with distributed data processing technologies such as Apache Spark or Apache Flink is highly desirable.
• A bachelors degree is preferred.
• We typically look for 7 to 10 years of relevant work experience.
• We require legal authorization to work in the United States without current or future sponsorship.

• We partner with product and field engineering teams to identify analytical questions and define experimentation needs.
• We lead the design and coding of software, algorithms, and automated workflows that cleanse, combine, and assess large datasets from diverse sources.
• We apply statistical methods, data mining, optimization, machine learning, and other analytical techniques to extract actionable insight from complex data.
• We develop and execute statistical and mathematical approaches that solve business problems and support broader initiatives.
• We build data-mining architectures, statistical reports, and analysis methods to surface trends in large datasets.
• We analyze historical customer behavior and product performance, and we create predictive models that anticipate future outcomes.
• We research and apply emerging data science concepts and techniques to support business decision-making.
• We prepare deliverables and presentations that clearly communicate methods, findings, and results.
• We design customer-focused models and optimization tools for large-scale projects using both streaming and stored data.
• We support production deployments, investigate customer issues, and assist with platform usage.
• We develop security features and help advance a DevSecOps culture.
• We improve tools used to identify and reduce production incidents.
• We build reusable software components and libraries that can serve multiple teams.
• We create self-contained microservices and APIs that support business logic.
• We follow established content management practices, design patterns, and coding standards.
• We exercise sound independent judgment in matters of significance.
• We maintain regular, punctual attendance and remain flexible as needed.
• We take on additional duties and responsibilities as assigned.
• We serve as a technical anchor and mentor within a globally distributed engineering team, providing guidance and architectural direction.

• AI
• DevSecOps
• Docker
• Fine-tuning
• Flink
• GitHub
• Support
• JIRA
• LLM
• Machine Learning
• MLOps
• Python
• Security
• Spark
• microservices
• Big Data
• RAG
• REST

More:

We are Comcast, a Fortune 30 global media and technology company, and our DataBee division delivers SaaS and subscription-based security solutions to large enterprises and the federal government. Our cybersecurity suite is built from Comcasts proven internal security technologies and is designed to strengthen security and compliance while helping customers control costs. In this role, you join a fast-paced, highly collaborative engineering organization where we encourage innovation, invest in ideas, and value an authentic workplace. The position is part of our award-winning technology team and may involve on-site collaboration depending on team needs, with remote consideration in some cases for candidates living more than 100 miles from the office. We offer a competitive base salary range, best-in-class benefits for eligible employees, and a broad Total Rewards package that supports physical, financial, and emotional well-being. We are an equal opportunity employer and consider qualified applicants without regard to protected characteristics.

last updated 33 week of 2026