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I'm Subhash, a Senior AI/ML Engineer with 8+ years of experience building and deploying agentic AI workflows and scalable AI solutions across finance, healthcare, and enterprise domains. I design LangGraph-based agent architectures and leverage agentic frameworks and orchestration patterns to execute complex business logic in production environments. I have a proven track record of translating business requirements into technical designs and implementable plans, partnering closely with business stakeholders and downstream execution teams to drive delivery of enterprise-scale transformation initiatives. I am proficient in developing LLM-powered multi-agent systems with robust data and context management patterns, ensuring reliable state handling, memory, and decision flow across agent workflows. I bring deep expertise in operationalizing LLM-powered systems through end-to-end LLMOps workflows, including monitoring, governance, hallucination detection, and prompt evaluation, ensuring high performance, scalability, and reliability. I excel at bridging the gap between data engineering, machine learning, and business stakeholders to deliver impactful, AI-driven solutions across platforms such as Azure, AWS, GCP, and Databricks.…I'm Subhash, a Senior AI/ML Engineer with 8+ years of experience building and deploying agentic AI workflows and scalable AI solutions across finance, healthcare, and enterprise domains. I design LangGraph-based agent architectures and leverage agentic frameworks and orchestration patterns to execute complex business logic in production environments. I have a proven track record of translating business requirements into technical designs and implementable plans, partnering closely with business stakeholders and downstream execution teams to drive delivery of enterprise-scale transformation initiatives. I am proficient in developing LLM-powered multi-agent systems with robust data and context management patterns, ensuring reliable state handling, memory, and decision flow across agent workflows. I bring deep expertise in operationalizing LLM-powered systems through end-to-end LLMOps workflows, including monitoring, governance, hallucination detection, and prompt evaluation, ensuring high performance, scalability, and reliability. I excel at bridging the gap between data engineering, machine learning, and business stakeholders to deliver impactful, AI-driven solutions across platforms such as Azure, AWS, GCP, and Databricks.

Subhash S

AI Engineer, AI Developer, Data Scientist, +2

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I'm Subhash, a Senior AI/ML Engineer with 8+ years of experience building and deploying agentic AI workflows and scalable AI solutions across finance, healthcare, and enterprise domains. I design LangGraph-based agent architectures and leverage agentic frameworks and orchestration patterns to execute complex business logic in production environments. I have a proven track record of translating business requirements into technical designs and implementable plans, partnering closely with business stakeholders and downstream execution teams to drive delivery of enterprise-scale transformation initiatives. I am proficient in developing LLM-powered multi-agent systems with robust data and context management patterns, ensuring reliable state handling, memory, and decision flow across agent workflows. I bring deep expertise in operationalizing LLM-powered systems through end-to-end LLMOps workflows, including monitoring, governance, hallucination detection, and prompt evaluation, ensuring high performance, scalability, and reliability. I excel at bridging the gap between data engineering, machine learning, and business stakeholders to deliver impactful, AI-driven solutions across platforms such as Azure, AWS, GCP, and Databricks.…I'm Subhash, a Senior AI/ML Engineer with 8+ years of experience building and deploying agentic AI workflows and scalable AI solutions across finance, healthcare, and enterprise domains. I design LangGraph-based agent architectures and leverage agentic frameworks and orchestration patterns to execute complex business logic in production environments. I have a proven track record of translating business requirements into technical designs and implementable plans, partnering closely with business stakeholders and downstream execution teams to drive delivery of enterprise-scale transformation initiatives. I am proficient in developing LLM-powered multi-agent systems with robust data and context management patterns, ensuring reliable state handling, memory, and decision flow across agent workflows. I bring deep expertise in operationalizing LLM-powered systems through end-to-end LLMOps workflows, including monitoring, governance, hallucination detection, and prompt evaluation, ensuring high performance, scalability, and reliability. I excel at bridging the gap between data engineering, machine learning, and business stakeholders to deliver impactful, AI-driven solutions across platforms such as Azure, AWS, GCP, and Databricks.

Available to hire

I’m Subhash, a Senior AI/ML Engineer with 8+ years of experience building and deploying agentic AI workflows and scalable AI solutions across finance, healthcare, and enterprise domains. I design LangGraph-based agent architectures and leverage agentic frameworks and orchestration patterns to execute complex business logic in production environments. I have a proven track record of translating business requirements into technical designs and implementable plans, partnering closely with business stakeholders and downstream execution teams to drive delivery of enterprise-scale transformation initiatives.

I am proficient in developing LLM-powered multi-agent systems with robust data and context management patterns, ensuring reliable state handling, memory, and decision flow across agent workflows. I bring deep expertise in operationalizing LLM-powered systems through end-to-end LLMOps workflows, including monitoring, governance, hallucination detection, and prompt evaluation, ensuring high performance, scalability, and reliability. I excel at bridging the gap between data engineering, machine learning, and business stakeholders to deliver impactful, AI-driven solutions across platforms such as Azure, AWS, GCP, and Databricks.

Skills

Experience Level

Expert

Expert

Expert

Expert

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Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at UBS

January 1, 2024 - Present

Designed and implemented LangGraph-based multi-agent architecture with Azure OpenAI (GPT-4o) to orchestrate complex investment workflows across Research and Portfolio agents for UBS Red. Built an Orchestrator Agent for intent parsing and inter-agent routing, enabling structured communication and reliable decision flow. Pre-processed 60K+ financial documents with PySpark and PyMuPDF, storing cleaned outputs in ADLS Gen2 and generated embeddings from FinBERT/Sentence-BERT indexed in Azure AI Search (hybrid vector + BM25) and FAISS, achieving improved retrieval precision. Developed an RAG-based Research Agent using LangChain and Azure OpenAI with sub-second latency and 88%+ retrieval accuracy. Implemented NER pipelines for financial entities and mapped portfolio holdings to CIO recommendations. Created MCP-based Portfolio Agent for real-time client data with dynamic analytics and decision support. Established an MCP server and tool registry with secure RBAC; designed cross-agent reasoning

ML Engineer at Intermountain Health

February 1, 2021 - August 1, 2023

Developed end-to-end ML pipelines on Google Cloud Platform for patient risk prediction and clinical forecasting using EHR/EMR data. Ingested 20M+ real-time records via Kafka and PySpark on Dataproc, engineered features from demographics, vitals, labs, and ICD-10 codes. Trained XGBoost, LightGBM, and Random Forest models on Vertex AI with cross-validation, achieving >90% AUC. Built Isolation Forest-based anomaly detection to improve data quality in EHR/EMR. Implemented Prophet-based forecasting for admissions and resource utilization. Applied SHAP/LIME explanations for interpretability; configured Vertex AI Model Monitoring for drift; automated retraining via Jenkins and Dockerized GKE deployments. Enabled Claude API narratives to explain patient risk while ensuring HIPAA-compliant data practices and automated audit trails.

ML Data Engineer at BMW Group

December 1, 2019 - February 1, 2021

Designed and supported a data platform consolidating 20TB+ data from multiple sources into an S3-based lakehouse. Built scalable ETL pipelines using AWS Glue and Databricks (PySpark, Spark SQL) and managed data quality with Delta Lake. Implemented Medallion architecture, advanced SQL in Redshift, and Airflow-based orchestration. Established automated data labeling and model monitoring workflows; integrated analytics-ready datasets for risk analysis and ML-driven insights.