AI Data & Knowledge Architect / Engineer

BCforward; Charlotte (NC); Hybrid; USD 76,000 - 108,000; Full time

Job summary

BCforward is seeking an experienced AI Data & Knowledge Architect/Engineer to develop, govern, and improve data and knowledge foundations supporting AI across Network Services. The role focuses on data modeling, governance, and scalable context management for AI-ready assets.

The candidate will partner with SMEs to capture domain knowledge, design scalable storage and retrieval of context, and ensure data quality and governance in a regulated enterprise environment.

Qualifications

• Experience engineering and managing structured and unstructured data for analytics, automation, search, or AI-enabled solutions.
• Strong understanding of data modeling, transformation, storage, and retrieval patterns for scalable, governed pipelines.
• Ability to define and apply standards for preparing data, documents, knowledge artifacts, metadata, and operational context for AI consumption.
• Experience establishing data quality controls, validation checks, and monitoring to improve trust, completeness, and consistency.
• Knowledge of preventative and detective controls for data, metadata, and knowledge management issues.
• Experience with knowledge sources such as documentation, standards, policies, configurations, runbooks, telemetry, and operational records.
• Ability to translate network operational knowledge into usable data and knowledge assets with SMEs.
• Working understanding of network technologies, infrastructure concepts, and operational service models.
• Experience defining ownership, lineage, freshness, retention, governance, and stewardship in a regulated enterprise.
• Familiarity with AI and retrieval-oriented preparation, including grounding, context structuring, metadata quality, and content readiness.
• Ability to design and implement scalable approaches for storing, governing, indexing, and retrieving data and knowledge assets.
• Strong analytical and problem-solving skills with root-cause analysis and sustainable remediation focus.
• Experience collaborating across engineering, architecture, operations, and governance stakeholders.
• Strong written and verbal communication with ability to document standards, controls, and usage guidance clearly.
• Experience operating in a fast-paced environment with evolving priorities and cross-functional dependencies.

Responsibilities

• Develop and maintain data and knowledge assets for AI and agentic use cases across Network Services, covering structured and unstructured sources.
• Define and apply standards for organizing documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge for AI consumption.
• Partner with product and service subject matter experts to capture network technologies, operational context, and domain knowledge to improve model grounding and decision quality.
• Design and implement scalable methods for storing, governing, indexing, and retrieving context assets for AI-enabled workflows.
• Establish and improve preventative and detective controls to reduce data, metadata, and knowledge quality issues and ensure freshness.
• Contribute to remediation by identifying upstream sources, defining corrective actions, and improving reliability at the source.
• Define and maintain expectations for ownership, lineage, freshness, stewardship, and governance across relevant domains.
• Build and enhance pipelines, transformations, validations, and services that improve quality and accessibility of data and knowledge assets.
• Create reusable templates, patterns, and guidance for knowledge artifacts, documentation standards, and context management.
• Align practices with enterprise controls and standards in partnership with engineering, architecture, operations, and governance teams.
• Monitor and communicate health, readiness, and quality of AI-relevant assets, including issues and remediation priorities.
• Continuously improve data and knowledge management to strengthen trust, reuse, traceability, and operational supportability.
• Document data definitions, controls, transformations, and usage considerations for reliable downstream consumption.

Skills

Data modeling

Data governance

Data quality controls

Metadata management

AI data prep

Documentation standards

Stakeholder collaboration

Networking know-how

Job description

Job Title: AI Data & Knowledge Architect / Engineer

Location: Chandler, AZ (Hybrid, 3 days onsite required). Local candidates only.

Duration: Contract – 12 months

Pay Range: $66.71/hr (W2)

Job ID: 411640

About BCforward

BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity.

Job Description

We are seeking an experienced AI Data & Knowledge Architect / Engineer to develop, govern, and improve the data and knowledge foundations that support AI and agentic capabilities across Network Services. The ideal candidate will have strong experience in data modeling, data governance, and scalable context management for AI consumption, and a proven ability to translate domain knowledge into reusable, AI-ready assets.

Responsibilities:

• Develop and maintain data and knowledge assets for AI and agentic use cases across Network Services, covering structured and unstructured sources.

• Define and apply standards for organizing documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge for AI consumption.

• Partner with product and service subject matter experts to capture network technologies, operational context, and domain knowledge to improve model grounding and decision quality.

• Design and implement scalable methods for storing, governing, indexing, and retrieving context assets for AI-enabled workflows.

• Establish and improve preventative and detective controls to reduce data, metadata, and knowledge quality issues and ensure freshness.

• Contribute to remediation by identifying upstream sources, defining corrective actions, and improving reliability at the source.

• Define and maintain expectations for ownership, lineage, freshness, stewardship, and governance across relevant domains.

• Build and enhance pipelines, transformations, validations, and services that improve quality and accessibility of data and knowledge assets.

• Create reusable templates, patterns, and guidance for knowledge artifacts, documentation standards, and context management.

• Align practices with enterprise controls and standards in partnership with engineering, architecture, operations, and governance teams.

• Monitor and communicate health, readiness, and quality of AI-relevant assets, including issues and remediation priorities.

• Continuously improve data and knowledge management to strengthen trust, reuse, traceability, and operational supportability.

• Document data definitions, controls, transformations, and usage considerations for reliable downstream consumption.

Required Skills & Qualifications:

• Experience engineering and managing structured and unstructured data for analytics, automation, search, or AI-enabled solutions.

• Strong understanding of data modeling, transformation, storage, and retrieval patterns for scalable, governed pipelines.

• Ability to define and apply standards for preparing data, documents, knowledge artifacts, metadata, and operational context for AI consumption.

• Experience establishing data quality controls, validation checks, and monitoring to improve trust, completeness, and consistency.

• Knowledge of preventative and detective controls for data, metadata, and knowledge management issues.

• Experience with knowledge sources such as documentation, standards, policies, configurations, runbooks, telemetry, and operational records.

• Ability to translate network operational knowledge into usable data and knowledge assets with SMEs.

• Working understanding of network technologies, infrastructure concepts, and operational service models.

• Experience defining ownership, lineage, freshness, retention, governance, and stewardship in a regulated enterprise.

• Familiarity with AI and retrieval-oriented preparation, including grounding, context structuring, metadata quality, and content readiness.

• Ability to design and implement scalable approaches for storing, governing, indexing, and retrieving data and knowledge assets.

• Strong analytical and problem-solving skills with root-cause analysis and sustainable remediation focus.

• Experience collaborating across engineering, architecture, operations, and governance stakeholders.

• Strong written and verbal communication with ability to document standards, controls, and usage guidance clearly.

• Experience operating in a fast-paced environment with evolving priorities and cross-functional dependencies.

Preferred Skills:

• Background in network services data domains and operational telemetry.

• Experience with enterprise data governance and stewardship frameworks.

Why BCforward?

At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to:

• Competitive compensation and benefits.

• Opportunities for growth with global clients.

• A supportive, inclusive culture that values innovation and people.

• Exposure to cutting-edge technologies and projects.

About Our Commitment

BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status.