Solution Architect

About the Program:

Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities.

About the Role:

As the Solution Architect, you'll design the backbone of the platform. You'll define the architecture for the data services storefront and own the DataCard governance framework that keeps our data trustworthy, documented, and compliant end to end. Working closely with the engineering team and the Delivery Owner, you'll translate governance and security requirements in a secure federal (IL4) environment into a clean, defensible technical design. It's a role for an architect who cares as much about data stewardship and governance as about elegant systems.

Key Responsibilities:

Own cross-pillar architectural integrity and AFS-Innodata interface coordination across the 24-week program

Design and stand up the DataCard governance framework: schema design, distribution-statement methodology (DoD Dir. 5230.24), provenance lineage

Deploy and configure ZenML multi-cloud orchestration stack per Innodata Layer 2 Multi-Cloud Architecture v3

Design taxonomy engine and sequestration controls architecture

Confirm NIST SP 800-53 Rev 5 control split between Innodata data-layer and AFS infrastructure-layer scope

Lead platform component run books and per-DataCard documentation in Phase E

Coordinate with AI Solutions Engineer on Kubernetes-adjacent data-layer DLP policy configuration

Coordinate with Backend Engineer on Databricks write-back schema and DataCard write-back path

Must-Have Qualifications:

Bachelor's degree in Computer Science, Data Engineering, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis.

10+ years total professional experience, 6+ years in data architecture or platform engineering

Databricks, Delta Lake, and MLflow — hands-on implementation experience, not conceptual

Data governance frameworks: DataCards, provenance, lineage, distribution statement controls

ZenML or equivalent ML orchestration tooling (Airflow or Prefect acceptable; must be willing to ramp ZenML quickly)

Working knowledge of IL4/IL5 boundary concepts, NIST SP 800-53 Rev 5, and DoD data classification requirements

Active Secret clearance with TS/SCI eligibility

Nice-to-Have Qualifications:

Prior Innodata or annotation platform architecture experience

MLflow model governance and registry hands-on experience

Ontology and taxonomy design for AI/ML training datasets

DoD Directive 5230.24 distribution statement implementation experience

The expected hourly salary range for this position is $70 to $75 p/hour, based on experience, skills, and qualifications.

Note to Candidates:

This role is the primary technical decision-maker on the program below the Delivery Owner. The SA is expected to make architectural calls independently within the established framework and surface only unresolved cross-cutting decisions to the Delivery Owner.