Applied AI Engineer - Customer Experience

Requirements

Your Journey: From Understanding to Automation

Phase 1: Master the Domain (Months 1-6)

• Resolve customer support tickets, manage escalations, and troubleshoot complex issues for enterprise clients
• Develop empathy for pain points through direct interactions
• Analyze codebase, patterns, and business impact while solving problems
• Identify repetitive tasks and build initial automation tools
  

Phase 2: Architect the Future (Months 6+)

• Design AI agents using LLMs, agentic frameworks, and vector databases for automated resolutions
• Create workflows for diagnosis, API interactions, and autonomous fixes
• Deploy ML models for predictive detection, root cause analysis, and proactive outreach
• Implement RAG, function calling, and multi-agent systems.
  

Key Responsibilities

Customer Success & Support (Phase 1 Focus):

• Resolve tickets via portal with timely, high-quality solutions
• Handle escalations and troubleshooting for critical operations
• Manage incident communications and technical explanations
• Participate in on-call rotations across time zones
• Own metrics: SLA adherence, first-call resolution, and satisfaction scores
  

AI & Automation Engineering (Growing Focus):

• Deploy AI systems using modern frameworks
• Build automation for multi-step scenarios
• Develop predictive models for issue prevention
• Create autonomous AI agents
• Reduce manual support through automation
  

Technical Innovation:

• Integrate AI tools to boost efficiency
• Experiment and contribute to AI-first culture
• Collaborate to embed customer learnings into the platform
  

What We're Looking For

Mindset & Skills:

• Entrepreneurial spirit: Turn problems into transformative solutions
• AI-first thinking: Excited to apply AI to business challenges
• Customer obsession: Driven to create exceptional experiences
• Systems thinking: Connect technical solutions to outcomes
• Strong engineering fundamentals in Python, JavaScript, or similar
• Knowledge of AI/ML, LLMs, frameworks, APIs, databases, and integrations
• Familiarity with data analysis tools.
  

Bonus Points:

• Experience with AI agents, automation, or CX platforms
• Background in data science, ML, or AI research
• Time in fast-growing SaaS companies
• Interest in logistics or enterprise software