
Principal AI Architect
1 week ago
Job Title: Technical Manager
Job Description:We are seeking a skilled technical professional to lead the design and delivery of an AI-powered solution, combining natural language processing, anomaly detection, generative AI/retrieval augmented generation, and rule engines on cloud platforms.
- Define reference architecture, make build/buy decisions, select, train, and operationalize NLP, anomaly/fraud models, and generative AI/RAG components.
- Establish human-in-the-loop, implement experiment tracking, model registry, CI/CD for models, automated evaluation, drift monitoring, rollback.
- Design retrieval pipelines, guardrails, and citation-based responses.
- Oversee feature store, labeling strategy, high-quality gold datasets, enforce DQ rules and lineage.
- Right-size SKUs, caching/batching, cost/per-token dashboards, SLOs for latency/throughput.
- Break down epics/stories, estimate and sequence work, unblock the team, run technical design reviews.
- Translate business policy into rule + ML ensembles, present options, risks, and trade-offs.
- Establish testing pyramid, performance targets, observability dashboards.
- Produce design docs, runbooks, SOPs, mentor engineers, uplift coding and review standards.
- 10+ years of software development experience, with at least 5 years leading AI/ML projects.
- Supervised/unsupervised modeling, anomaly detection, NLP, OCR pipelines; evaluation design (precision/recall, ROC/PR).
- LangChain/LangGraph; embeddings; vector databases; prompt engineering & safety patterns.
- MLflow, model registry, online/offline evals, data/version management; CI/CD for models.
- Delta Lake/Lakehouse, Azure Data Lake Gen2, Databricks/ADF, schema/versioning, Great Expectations/Deequ.
- Python, eventing, containerization, APIM.
- Cognitive Search, Azure OpenAI, Key Vault, Monitor/App Insights, Purview, Cosmos DB/Azure SQL.
- Technical decision-making, cross-team coordination, stakeholder communication, mentoring.
- Certifications in AI/ML disciplines.
- Hands-on experience with explainable AI and AI governance.
- Familiarity with regulatory compliance standards for financial data.
- Bachelor's Degree in Computer Science or related science field or equivalent.
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