AI Engineer
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Job Description
AI Engineer developing and productionizing AI systems for payment failure analysis and operational efficiency at fintech. Designing scalable model components for autonomous financial incident analysis.
Responsibilities:
- Design and deploy a locally hosted LLM-powered agent for autonomous payment failure analysis
- Build internal LLM infrastructure with no external API dependency for core workflows
- Develop structured pipelines for root cause identification across transaction failures
- Automate Level 1 incident investigations
- Generate standardized root cause analysis (RCA) reports
- Optimize model performance to reduce Mean Time to Resolution (MTTR)
- Develop scalable training and inference pipelines
- Create reusable model components adopted across multiple use cases
- Reduce time-to-deploy new AI applications
- Decrease reliance on external AI APIs through internal model development
- Implement monitoring systems for latency, drift, and model performance
- Deploy at least two additional AI use cases (e.g., chatbot, automated reporting, issue clustering)
- Ensure ≥99.9% production uptime
- Maintain inference latency within defined thresholds
- Establish retraining cadence and continuous performance evaluation
- Deliver measurable efficiency improvements in operational workflows
- Implement version-controlled datasets and model versioning
- Define evaluation benchmarks (precision, recall, accuracy thresholds)
- Implement automated drift detection
- Document model architecture and training processes
- Ensure zero preventable production-critical failures due to model design
- Ensure personal information of customers, employees, and other individuals processed and protected in line with applicable data privacy policies.
Requirements:
- 4–7+ years in Machine Learning / AI Engineering
- Strong Python proficiency (PyTorch, TensorFlow, Hugging Face)
- Experience working with LLMs (fine-tuning, RAG, embeddings, retrieval systems)
- Experience deploying ML systems in production (Docker, Kubernetes, CI/CD)
- Experience building inference pipelines and monitoring systems
- Strong understanding of evaluation metrics and ML governance practices
- Experience working with large-scale structured and unstructured datasets
- Strong preference for previous fintech or payments experience
Benefits:
- Health insurance
- Flexible work arrangements
- Professional development opportunities
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