AI Solutions Engineer
US$75 – US$80 / hr base salary
Posted 9 Jul 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 6+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
| Base salary | US$75 – US$80 / hr |
|---|
Field of studyComputer Science, Data Science, Machine learning (or related)
Study levelBachelor's
Study levelMaster's
Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
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 AI Solutions Engineer, you'll bring the platform's AI capabilities to life. You'll integrate synthetic data generation into the pipeline, stand up and tune the annotation toolchain, and orchestrate reproducible ML workflows that the rest of the team can build on. You'll partner with the Solution Architect and Data/Annotation Engineer to turn raw corpora into high-quality, model-ready data. This role suits an engineer who's fluent across modern AI tooling and enjoys making sophisticated ML infrastructure actually work in production.
Key Responsibilities:
- Configure and validate native AI-assistive features across bundled platform components (Dataset Explorer, DataCard Service, Annotation Platform)
- Integrate and tune SAM 2 for full-motion video annotation: object tracking, segmentation calibration, confidence threshold configuration
- Implement Frontier model API integration for synthetic data fidelity validation: prompt engineering, response validation, quality scoring
- Configure AI-assisted annotation features: confidence scoring, auto-escalation triggers, model-assisted label suggestion
- Implement ICAM / OIDC authentication integration with AFS identity framework
- Configure data-layer DLP policies above the AFS-managed DLP infrastructure substrate
- Configure NiFi FMV codec validation layer (H.264, H.265, MPEG-4) above AFS-managed substrate
- Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C
Must-Have Qualifications: