Opstree Solutions - Senior AI/ML & Data Engineer

Azure OpenAI Framework & LLM Engineering:Design and implement the end-to-end Azure OpenAI deployment architecture.Build the Business Logic Prompt Builder layer: prompt templates, chain-of-thought patterns, and system prompt configurations.Implement RAG pipelines using Azure AI Search and vector stores to ground financial advice in live user transaction data.Design and implement the Validation Layer (Guardrails): out-of-scope detection, hallucination filtering, and Retry/Reject logic.Configure Azure OpenAI Content Filters and custom blocklists aligned to PCI DSS 4.0, GDPR, and banking AI governance requirements.Implement human-in-the-loop controls for high-impact use cases and confidence scoring. Data Engineering & Analytics:Design and build real-time and batch pipelines ingesting transaction data from Oracle DB on Azure, Azure Event Hub, and Kafka-on-AKS.Engineer financial features per use case: rolling spend aggregations, time-series features for balance forecasting, and anomaly detection signals.Build and maintain the RAG knowledge base: curate, chunk, embed, and index financial product data.Implement PII masking, column-level encryption, and full data lineage.Build AI performance analytics: response accuracy dashboards, model input drift detection, and bias monitoring. Security, Compliance & Governance:Enforce no-public-internet AOAI access Private Endpoint, VNet integration, NSG rules, DNS private zones.Implement audit logging for all AI interactions to Azure Log Analytics with PII masking.Own HIGH-priority AI Risk Assessment remediation.Maintain Azure ML model registry, model versioning, and deployment approval pipeline. Tech Stack: Azure OpenAI, Prompt Engineering, RAG/Vector Search, LangChain, Semantic Kernel, Azure AI Search, Python, PySpark, Azure Databricks, Apache Kafka, Azure Event Hubs, Oracle DB, Redis, Azure Data Factory, Delta Lake, Azure Kubernetes Service, CI/CD (Azure DevOps), PCI DSS, GDPR.

5 years of experience in AI/software development, with at least 4 years building and shipping production LLM or generative AI applications.Deep hands-on experience with Azure OpenAI Service.Strong data engineering background: real-time streaming, financial-scale batch pipelines, and SQL/PySpark.Experience deploying AI and data workloads on AKS with enterprise security controls.Proven track record implementing guardrails and compliance controls in regulated environments.Experience with MLOps: model versioning, performance monitoring, and CI/CD pipelines.Strong understanding of PCI DSS 4.0, GDPR, and banking AI governance.Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or equivalent experience. .