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# Software Engineer (AI Data Engineering)

- **Company:** EvolutionIQ
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $170,000 - $185,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Code Coverage, Code Generation, Code Review, Data Validation, Information Engineering, Cursor, Database Development, Python (Programming Language), Rapid Prototyping Process, Multi-Agent Systems, Backend, Agentic-AI, Data Layers, Data Pipelines
- **Published:** November 14, 2026
- **Apply:** https://job-boards.greenhouse.io/evolutioniq/jobs/6261926004

## About the Role

* 2+ years of engineering experience going through the full feature development life cycle: Working with product managers, deciding scope, designing data models and pipeline architectures. Python and SQL Development is a plus
 * Proven fluency in using agentic coding tools like Cursor AI and/or claude
 * Experience designing, building and launching backend architectures that support multi-tenant, multi-user scenarios through pipeline performance and data quality checks
 * Ability to remain agile and move between rapid prototyping and stable production development
 * Ability to write technical design documents, perform code reviews, and maintain state of the art engineering practices
 * You know the critical questions to ask in order to understand a client's business problem and can show the business impact of your technical solutions through data
 * You have crisp written and verbal communication skills and the ability to effectively correspond between technical and non-technical audiences
 * Excellent collaboration skills and are open to giving and receiving critical feedback across teams
 * You have an eye towards analytics and helping to enable data driven decision making, Do you have at least 3 years of Python coding experience shipping code into production in a team development environment?*

## Description

* Orchestrate High-Velocity Workflows: Leverage advanced agentic coding tools (e.g., Cursor, multi-agent environments) to dramatically accelerate feature prototyping, code generation, and test coverage.
 * Own the Guardrails & Quality: Act as the ultimate reviewer and architect; define the specifications, establish repo-context guardrails, and review AI-accelerated output for hidden security risks, scale bottlenecks, and architectural alignment.
 * Build Scalable Application and Data Layers: Design, build, and maintain our data pipelines and application to service our hundreds of users.
 * Bridging the Data: Partner closely with product, client services, and data science teams to transform raw pipeline outputs into meaning.
 * Drive Greenfield Engineering: Take complete ownership of designing, building, and launching enterprise-grade applications, moving fluidly between rapid prototyping and bulletproof production systems.