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Principal AI Engineer with 20 years of enterprise software engineering experience, including 5+ years building production ML and data platforms and 3+ years designing and operating Generative AI and Agentic AI systems in regulated banking and financial services. Hands-on across LLM-based conversational AI and multi-agent workflows on AWS Bedrock, integrating agent runtimes and event-driven serverless pipelines. Led end-to-end AI implementations in BaFin-regulated environments spanning AML, KYC, and credit risk, combining hands-on engineering with architecture governance and stakeholder leadership. Delivered production reliability, audit-ready evidence, and strong compliance outcomes through robust evaluation frameworks, explainability, and secure AI practices.…Principal AI Engineer with 20 years of enterprise software engineering experience, including 5+ years building production ML and data platforms and 3+ years designing and operating Generative AI and Agentic AI systems in regulated banking and financial services. Hands-on across LLM-based conversational AI and multi-agent workflows on AWS Bedrock, integrating agent runtimes and event-driven serverless pipelines. Led end-to-end AI implementations in BaFin-regulated environments spanning AML, KYC, and credit risk, combining hands-on engineering with architecture governance and stakeholder leadership. Delivered production reliability, audit-ready evidence, and strong compliance outcomes through robust evaluation frameworks, explainability, and secure AI practices.

Valli Shaikhk

AI Engineer, Software Engineer, Data Engineer, +2

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Principal AI Engineer with 20 years of enterprise software engineering experience, including 5+ years building production ML and data platforms and 3+ years designing and operating Generative AI and Agentic AI systems in regulated banking and financial services. Hands-on across LLM-based conversational AI and multi-agent workflows on AWS Bedrock, integrating agent runtimes and event-driven serverless pipelines. Led end-to-end AI implementations in BaFin-regulated environments spanning AML, KYC, and credit risk, combining hands-on engineering with architecture governance and stakeholder leadership. Delivered production reliability, audit-ready evidence, and strong compliance outcomes through robust evaluation frameworks, explainability, and secure AI practices.…Principal AI Engineer with 20 years of enterprise software engineering experience, including 5+ years building production ML and data platforms and 3+ years designing and operating Generative AI and Agentic AI systems in regulated banking and financial services. Hands-on across LLM-based conversational AI and multi-agent workflows on AWS Bedrock, integrating agent runtimes and event-driven serverless pipelines. Led end-to-end AI implementations in BaFin-regulated environments spanning AML, KYC, and credit risk, combining hands-on engineering with architecture governance and stakeholder leadership. Delivered production reliability, audit-ready evidence, and strong compliance outcomes through robust evaluation frameworks, explainability, and secure AI practices.

Available to hire

Principal AI Engineer with 20 years of enterprise software engineering experience, including 5+ years building production ML and data platforms and 3+ years designing and operating Generative AI and Agentic AI systems in regulated banking and financial services. Hands-on across LLM-based conversational AI and multi-agent workflows on AWS Bedrock, integrating agent runtimes and event-driven serverless pipelines.

Led end-to-end AI implementations in BaFin-regulated environments spanning AML, KYC, and credit risk, combining hands-on engineering with architecture governance and stakeholder leadership. Delivered production reliability, audit-ready evidence, and strong compliance outcomes through robust evaluation frameworks, explainability, and secure AI practices.

Skills

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Intermediate

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Work Experience

Principal AI Engineer at German Tier-1 Bank

March 20, 2025 - Present

Designed and developed enterprise-scale agentic AI and generative AI credit-decisioning platform on Azure (Azure OpenAI, Azure ML, DataBricks) processing 10K+ multimodal financial documents daily for document intelligence, credit risk, underwriting automation, explainable AI, and governance controls. Implemented scalable agentic systems using Crew AI, LangGraph, Semantic Kernel, and Microsoft PromptFlow with Model Context Protocol (MCP) to support autonomous analysis, policy validation, exception handling, and underwriting recommendations under human-in-the-loop controls. Built hybrid retrieval and generation approaches (Hybrid RAG, Graph RAG, Agentic RAG, CRAG) with contextual retrieval over multimodal documents to convert unstructured borrower documents into risk-ready underwriting insights. Engineered multimodal document intelligence pipelines in Python and PySpark on DataBricks, orchestrated with Azure Data Factory across 12+ financial document types, achieving 91% extraction accu

Principal AI Engineer at German Tier-1 Bank

January 1, 2024 - February 1, 2025

Designed and deployed a production-grade conversational multi-agent platform on Google Vertex AI, LangGraph, Crew AI, and Model Context Protocol (MCP) orchestrating five specialized AI agents for AML/KYC workflows, achieving 94% extraction accuracy and 45% reduction in false positives across 10K+ annual cases. Architected deterministic agent workflows with guardrails, human-in-the-loop approvals, fallback strategies, intent recovery, and agent handoff/escalation for secure and compliant voice/chat interactions in BaFin-regulated environments. Developed Python-based agent services, tool integrations, and REST APIs enabling agent-to-tool communication, policy validation, and event-driven workflow orchestration. Built hybrid RAG using Vertex AI Vector Search, semantic re-ranking, and contextual retrieval over 500+ AML/CFT policy documents to improve grounded responses and regulatory decision accuracy. Deployed agent services on GKE and Cloud Run with Cloud SQL, Cloud Storage, Artifact Re

Senior ML Data Engineer at German Tier-1 Telecom

September 1, 2021 - December 1, 2023

Built a DataBricks Customer 360 platform unifying CRM, billing, network events, care interactions, and digital activity via PySpark/Delta Lake ETL to serve reusable feature stores for churn, CLV, and analytics workloads. Engineered Spark structured streaming pipelines ingesting high-volume customer interaction events from Kafka with watermarking and exactly-once semantics, surfacing churn signals in near real time. Operationalized churn and CLV serving pipelines (PySpark, DataBricks ML, XGBoost) to DataBricks and SageMaker endpoints to support real-time retention campaigns. Built reusable PySpark feature engineering libraries and automated data quality gates (Great Expectations, Delta constraints, DataBricks workflows) improving pipeline reliability and reducing recurring data quality incidents. Implemented end-to-end ML observability (Prometheus, Grafana, CloudWatch, OpenTelemetry) tracking feature/concept drift, latency, throughput, and model performance to reduce incident detection

Senior ML Engineer at German Tier-1 E-commerce

March 1, 2018 - August 1, 2021

Designed AWS-based data and ML platforms enabling personalization at scale. Developed recommendation and segmentation models (K-means, TensorFlow), improving conversions by 18%. Automated ML deployment and retraining using SageMaker, Docker, Airflow, and CodePipeline. Designed ETL workflows with AWS Glue, Lambda, and Step Functions for near-real-time ingestion and transformation. Implemented data-quality validation, feature management, and reporting using Glue Data Catalog, Feature Store, Athena, and QuickSight.

Enterprise Software Architecture & Engineering

December 1, 2005 - January 1, 2018

Architected event-driven microservices (Spring Boot, Kafka, MongoDB) supporting platforms with 10M+ transactions/day across telecom, e-commerce, and aviation, improving scalability and reliability by 40%+. Designed high-performance REST APIs and secure enterprise applications (Spring, OAuth 2, JWT, circuit breakers, retry, bulkheads), reducing security incidents and integration defects by 30–40%. Led engineering teams (5–15), established CI/CD pipelines, centralized logging, and monitoring, reducing deployment cycle time by 50%.