Senior AI Engineer
Bengaluru · Senior
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Job description
- Design and maintain intelligent document pipelines for mortgage artefacts — loan packages, appraisals, title reports, closing disclosures — covering classification, splitting, field extraction, and audit tagging using LLMs + OCR.
- Build and optimise RAG (Retrieval-Augmented Generation) workflows for structured credit data including chunking strategies, embedding models, and vector store management.
- Collaborate with the architect to evaluate and integrate AI coding assistants (GitHub Copilot, Cursor, Claude Code), automated PR review bots, and test-case generation pipelines into existing Forgejo/Jenkins CI/CD workflows.
- Develop prompt engineering standards, fine-tuning strategies, and model evaluation frameworks aligned with internal SDLC quality gates.
- Own MLOps infrastructure: model versioning, A/B testing, drift detection, and observability on GCP (Vertex AI, Cloud Run, BigQuery ML).
- Drive data analytics initiatives — building LLM-powered reporting layers, anomaly detection, and insights extraction from loan performance data.
- Establish AI engineering best practices, conduct technical spike reviews, and mentor junior/intern engineers.
- Stay ahead of LLM landscape shifts (open-weight models, multimodal, agents) and present actionable adoption proposals to leadership.
- Independently scope and deliver AI features end-to-end: from data ingestion to deployed API to monitoring dashboard.
- Lead design reviews for AI components; document architectural decisions with clear trade-off analysis.
- Demonstrate measurable impact — extraction accuracy, latency SLOs, developer time saved — with quantified baselines.
- Proactively identify risks in LLM outputs (hallucination, PII leakage, compliance edge cases) and implement mitigation guardrails.
- Contribute to org-wide AI adoption playbook and internal knowledge base.
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