Senior AI Engineer

Zinier empowers frontline deskless workers globally through technology. We're looking for a pragmatic AI engineer to design and deploy AI solutions across enterprise functions, from operations to customer success, without over-engineering.

Key Responsibilities:

• Design appropriate solutions by assessing each use case: data aggregation, dashboards, rule engines, workflow automation, or AI systems based on actual need.
• Ship functional prototypes within 30 days; validate with real users and iterate rapidly.
• Build multi-agent AI architectures when justified by complexity and cost analysis.
• Score and prioritize opportunities using impact, feasibility, and time-to-value frameworks.
• Transition validated prototypes to production-grade systems with Platform Engineering.
• Create reusable infrastructure, templates, and patterns for departmental AI adoption.
• Document implementation economics for all solutions to inform leadership decisions.
• Train teams and cultivate internal AI champions across departments.

Required Qualifications:

• Deep understanding of neural networks, generative AI mechanics, and transformer models.
• Proficiency in modern programming languages for building solutions and data pipelines.
• Deep working knowledge of Claude (including Claude Code CLI), prompt architecture, and tool-use patterns.
• Demonstrated experience building multi-agent systems with orchestration and autonomous workflows.
• Comprehensive understanding of token economics and cost optimization.
• Rapid prototyping with disciplined, hypothesis-driven experimentation.
• 3+ years software engineering experience substantively focused on AI/ML or LLM applications.

Preferred Qualifications:

• Multi-agent frameworks: CrewAI, AutoGen, LangGraph, or custom architectures.
• Agent harness patterns: tool registration, context management, memory systems.
• Automation platforms: n8n, Zapier, Make.
• RAG architectures and vector databases (Pinecone, Weaviate, ChromaDB).
• Domain experience: FSM, enterprise SaaS, workforce management.
• MCP server development; JavaScript/TypeScript; analytics platforms (QuickSight, Tableau, Looker); SQL.

90-Day Expectations:

• Day 30: Two initial tools shipped; embedded across functions.
• Day 60: Three+ tools in active use; teams trained; playbook drafted.
• Day 90: Quarterly roadmap presented; impact metrics established; scaling recommendations.

This isn't a research role. You'll be shipping working prototypes in your first 30 days.