Engineer 6, Machine Learning, Data & AI

Blueface Ltd; Philadelphia (Philadelphia County); On-site; USD 224,000 - 352,000; Full time

Job summary

Blueface Ltd is seeking a visionary Senior Technologist, Data & Agentic AI Enablement to shape the enterprise data ecosystem and accelerate AI‑driven experiences. This leadership role drives data preparation for an Agentic AI future, ensuring data is trusted, discoverable, semantically rich, governed, and consumable by AI agents across the engineering lifecycle.

The role partners with Data Engineering, Data Platforms, Enterprise Architecture, Security, Product, and AI teams to define

Qualifications

• Qualifications + years of experience in Data Architecture, Data Engineering, Enterprise Architecture, or related technology disciplines.
• Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.
• Deep understanding of modern data architectures: data warehouses, data lakes, lakehouses, and data mesh concepts.
• Experience with AI technologies, including LLMs, RAG architectures, vector databases, agent frameworks, and AI orchestration platforms.
• Knowledge of modern software engineering, DevSecOps, CI/CD, and cloud‑native architectures.

Responsibilities

• Define enterprise AI/Agentic AI strategy and reference architectures for data platforms.
• Collaborate with Security, Privacy, and Risk teams to ensure responsible AI and secure data access practices.
• Lead governance for data lineage, quality, explainability, and auditability in AI deployments.
• Drive data product design and semantic models to enable AI reasoning and automation.
• Partner with Data Platform, Engineering, Analytics, and Product teams to align technology roadmaps.

Skills

Agentic AI

AI Adoption

Data Architecture Development

Data Engineering

Data Strategies

Enterprise Data

Education

Bachelor's Degree

Job description

Job Summary

We are seeking a visionary Senior Technologist, Data & Agentic AI Enablement to shape the future of our enterprise data ecosystem and accelerate the next generation of AI‑driven experiences. This enterprise leadership role is responsible for two complementary missions: Preparing enterprise data for an Agentic AI future, ensuring data is trusted, discoverable, semantically rich, governed, and consumable by AI agents. Transforming data engineering through Agentic AI, embedding AI across the data engineering lifecycle to improve productivity, quality, reliability, and speed of delivery. The successful candidate will define the architecture, standards, and engineering patterns that enable AI to become an active participant in the design, development, testing, operation, and optimization of enterprise data platforms. This highly influential role partners closely with Data Engineering, Data Platforms, Enterprise Architecture, Security, Product, and AI teams to accelerate data modernization and AI‑enabled business transformation.

Agentic AI Transformation of Data Engineering

• Define the enterprise roadmap for incorporating AI agents into data engineering workflows, platform operations, and software delivery.
• Partner with platform engineering teams to integrate AI capabilities into CI/CD, Infrastructure-as-Code (IaC), and DevSecOps practices.
• Evaluate emerging agent frameworks, copilots, and autonomous engineering platforms for enterprise adoption.
• Establish best practices and governance for AI‑assisted engineering and operational processes.

Enterprise Data Strategy for AI & Agentic Systems

• Define principles and reference architectures that enable AI agents to discover, access, understand, and act upon enterprise data safely and effectively.
• Partner with business and technology leaders to identify high‑value opportunities for Agentic AI solutions.
• Establish enterprise standards that align data, AI, and business strategies.

Data Architecture & AI Readiness

• Establish standards that ensure data is: Discoverable
• Well‑described and semantically rich
• Governed and trusted
• Accessible through standardized interfaces
• Consumable by both people and AI agents
• Drive adoption of metadata‑driven architectures, semantic models, knowledge graphs, and business ontologies.
• Ensure enterprise data products support machine‑to‑machine interactions in addition to traditional analytics use cases.

Agentic Data Enablement

• Establish standards for exposing enterprise data through APIs, semantic layers, data products, and retrieval systems.
• Retrieval‑Augmented Generation (RAG)
• Agent orchestration platforms
• Tool and API discovery
• Vector‑based retrieval architectures
• Context management and memory frameworks
• Develop patterns that allow AI agents to access enterprise knowledge securely and responsibly.

Data Governance & Trust

• Establish controls for data lineage, provenance, quality, explainability, and auditability.
• Partner with Security, Privacy, and Risk teams to implement responsible AI controls and secure data access practices.
• Define trust frameworks that enable AI agents to operate within approved business guardrails.

Semantic Layer & Knowledge Management

• Lead development of enterprise semantic models and shared business definitions.
• Improve metadata quality, business context, and knowledge accessibility across the organization.
• Advance enterprise knowledge management practices that enhance AI reasoning, discovery, and decision support.

Platform & Ecosystem Alignment

• Partner with Data Platform, Engineering, Analytics, and Product teams to align technology roadmaps.
• Collaborate with BI and analytics teams to maintain consistent business metrics and semantic definitions across human and AI consumers.
• Influence technology investments that enable future AI and Agentic AI capabilities.

Innovation & Thought Leadership

• Monitor emerging trends in AI, Agentic Systems, Data Architecture, and Knowledge Management.
• Evaluate innovative technologies and identify strategic adoption opportunities.
• Advise executive leadership on enterprise AI strategy and future‑state architecture.

Qualifications + years of experience

Qualifications + years of experience in Data Architecture, Data Engineering, Enterprise Architecture, or related technology disciplines. Proven experience designing and scaling enterprise data ecosystems. Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives. Demonstrated success influencing outcomes across large, matrixed organizations. Technical Expertise: Deep understanding of modern data architectures, including data warehouses, data lakes, lakehouses, and data mesh concepts. Expertise in metadata management, semantic modeling, data governance, and data product design. Strong understanding of APIs, event‑driven architectures, and interoperability standards. Experience with AI technologies, including LLMs, RAG architectures, vector databases, agent frameworks, and AI orchestration platforms. Knowledge of modern software engineering, DevSecOps, CI/CD, and cloud‑native architectures. Leadership & Communication: Strong executive communication and stakeholder management skills. Ability to translate emerging technologies into practical enterprise strategies. Proven ability to lead through influence across business and technology organizations. Demonstrated thought leadership in data, AI, or enterprise architecture domains.

Preferred Candidate Profile

A strategic technology leader with deep expertise in enterprise data architecture and a passion for advancing AI adoption. This individual combines strong technical vision, architectural leadership, and business acumen to help the organization build a trusted, AI‑ready data foundation while transforming the way engineering teams work through Agentic AI.

Disclaimer

This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.

Skills

• Agentic AI
• AI Adoption
• Data Architecture Development
• Data Engineering
• Data Strategies
• Enterprise Data

Compensation

This job can be performed in Virginia, and District of Columbia with a Pay Range of $224,190.44 - $351,571.37. Comcast intends to offer the selected candidate base pay within this range, dependent on job‑related, non‑discriminatory factors such as experience.

The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.

Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work.

Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non‑sales positions are eligible for a Bonus.

Additionally, Comcast provides best‑in‑class Benefits to eligible employees.

We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always‑on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life.

Please visit the compensation and benefits summary on our careers site for more details.

Education

Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.

Certifications (if applicable)

Relevant Work Experience

15 Years +

Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.

At Comcast , you have the power to connect the world. Your career options are endless as you grow in your career. Explore your future with access to a variety of teams, locations, and resources in an expanding network. You can also explore additional opportunities at our company, NBCUniversal.