Live opening · Posted 16 days ago
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Description supplied by the original job listing.
Responsibilities:
Build and deploy AI/ML solutions using Google Vertex AI on GCP.
Implement AI guardrails, governance, monitoring, evaluation gating, and responsible AI practices.
Deployment experience with GKE, Cloud Run, Docker, Kubernetes, CI/CD pipelines, MLOps, and LLMOps.
Implement security controls (RBAC, data redaction, PII masking, secrets management, and AI security governance).
Requirements:
Advanced Python development (FastAPI, Pandas, NumPy, PyTest, REST APIs).
Experience with OCR/IDP tools (Google Document AI, Tesseract, Azure Document Intelligence, Amazon Textract).
Hands-on with NER, document classification, embeddings, semantic search, and NLP pipelines.
Knowledge of fuzzy matching algorithms (Jaro-Winkler, Levenshtein, Damerau-Levenshtein, Jaccard, Cosine, TF-IDF, FuzzyWuzzy/RapidFuzz).
Familiarity with AI observability tools (Braintrust, Arize Phoenix, Promptfoo, Galileo, DeepEval, Ragas, Langfuse, and LangSmith).
Hands-on with LangGraph, Agentic AI, and Google ADK.
Expertise in LLM evaluation frameworks (trajectory/trace-based, tool-calling, Pass@k multi-run, LLM-as-a-Judge).
Strong skills in prompt engineering, RAG, knowledge graphs, semantic modeling, and vector databases.
Strong analytical, problem-solving, stakeholder communication, and solution architecture skills.
Experience: 7-10 years.
Experience
7-10 yrs
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