Senior Data & AI Engineer
- Compensation
- Not disclosed
- Location
- United States
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Part time
- Experience
- 5+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 5+ years in data engineering, backend engineering, or a related field
- Demonstrated experience deploying AI applications used by teams or customers
- Strong Python and SQL skills
- Experience with APIs, authentication, data pipelines, relational databases, and cloud infrastructure
- Practical understanding of retrieval-augmented generation, tool calling, structured outputs, and evaluation
- Experience with testing, version control, monitoring, and secure credential management
Nice to have
- Creator economy, influencer marketing, advertising technology, or SaaS
- Integrating CRM, financial, marketing, or operational systems
- Entity resolution, data modeling, and internal tool development
Full description
Location: Remote (U.S.)
Employment Type: Part-Time Contract, Initial Three-Month Engagement
Department: Product & Technology
Reports To: Head of Product
About NeoReach
NeoReach is a creator-technology company and influencer marketing leader trusted by Fortune 500 brands, global enterprises, and disruptive startups to deliver campaigns that move culture and drive business outcomes.
We combine agency expertise with proprietary creator-data infrastructure, performance tools, and AI-enabled workflows. Our ecosystem includes Influencers.com, a platform helping creators grow their businesses and unlock new opportunities.
We’re seeking an experienced engineer to strengthen our data infrastructure and build practical AI-powered tools.
Role Overview
The Senior Data & AI Engineer will connect business systems, improve data quality, and develop reliable tools that help teams work efficiently and make better decisions.
This is a hands-on individual contributor role, owning work from discovery through deployment. You will work directly with product leadership and collaborate with engineering and business teams to deliver focused solutions with measurable impact.
The initial engagement will prioritize a defined data integration and an AI-enabled workflow, with scope and milestones established at kickoff.
Key Responsibilities
Data Infrastructure and Integrations
- Assess existing data sources and workflows to identify gaps and opportunities
- Build integrations connecting APIs, databases, and business applications
- Standardize records, resolve duplicates, and establish consistent data definitions
- Implement validation, monitoring, and error handling
AI Tools and Automation
- Build tools for research, information retrieval, analysis, and recurring workflows
- Connect AI applications to approved internal systems and data
- Use AI coding tools to accelerate development while maintaining quality and reliability
- Evaluate accuracy, usefulness, and cost, with appropriate access controls and human review
Product Development and Delivery
- Translate business requirements into realistic technical milestones
- Ship prototypes, incorporate user feedback, and deploy successful tools into production
- Communicate progress, tradeoffs, and blockers
- Measure adoption, time savings, and operational improvements
Documentation and Knowledge Transfer
- Maintain company-owned code, architecture documentation, and deployment instructions