
Agentic AI Engineer | Gen AI Engineer | ML Engineer | Data Engineer
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- 10713 Berlin
- Europa
- ur | en | de
- 12.03.2025
Kurzvorstellung
Qualifikationen
Projekt‐ & Berufserfahrung
12/2022 – offen
Tätigkeitsbeschreibung
Designed, constructed, and deployed AI agents for client interactions, providing accurate financial information
and personalized responses.
● Implemented AI-driven risk management processes, analyzing large datasets to identify potential risks and
opportunities.
● Developed AI-powered systems for automated financial document processing, achieving 97% accuracy.
● Utilized Generative AI tools to assist developers in code writing, debugging, and documentation.
● Implemented Retrieval Augmented Generation (RAG) to improve the quality of chatbot responses.
● Integrated external tools with AI agents to enhance functionality.
● Developed client briefing generators using LLMs.
● Implemented autonomous AI agents for regulatory compliance monitoring and reporting.
● Worked with large language models to improve customer satisfaction.
Lead Developer
12/2021 – 12/2022
Tätigkeitsbeschreibung
Developed and deployed fraud detection models on Vertex AI, reducing false positives by 20% and safeguarding
transactions worth $50M.
● Implemented scalable ML pipelines for real-time fraud detection across 1M+ daily transactions.
● Fine-tuned machine learning and deep learning models using hyperparameter tuning and cross-validation,
ensuring high accuracy and effectiveness.
● Implemented MLOps practices to automate model deployment, monitoring, and retraining within GCP.
Machine Learning Engineer
12/2020 – 12/2021
Tätigkeitsbeschreibung
Engineered and deployed machine learning models to predict customer churn, achieving 85% accuracy.
● Utilized logistic regression, decision trees, random forests, and gradient boosting for churn prediction.
● Developed and engineered features from customer data sources, including behavioral patterns and usage
metrics.
● Leveraged Vertex AI and BigQuery for model training and data analysis.
● Implemented MLOps practices for automation.
● Enabled targeted customer retention campaigns, reducing churn by 15%.
Machine Learning Engineer
12/2004 – 7/2021
Tätigkeitsbeschreibung
Designed scalable microservices using Spring Boot and Kubernetes for enterprise clients.
● Built REST APIs integrated with Kafka, improving system response times by 40%.
● Developed and documented REST APIs using Swagger and ReadyAPI.
● Implemented OAuth2 for secure authentication and authorization.
● Deployed and managed microservices on AWS and GCP using Terraform.
● Automated CI/CD pipelines, reducing build times by 20%.
● Implemented monitoring and observability solutions using Prometheus, Grafana, and Splunk.
● Coordinated release management and deployment activities.
● Developed database layers using JPA, Hibernate, Oracle, and MySQL.
Solution Architekt
Ausbildung
Osmania University
India
Über mich
My technical toolkit includes MLflow for experiment tracking, and CI/CD pipelines for efficient AI deployments. I am proficient in containerization and orchestration using Docker, Kubernetes, and Helm, with a strong focus on scalability, resource management, and automation of ML workflows using Kubeflow.
Furthermore, I have a solid understanding of software development methodologies, particularly Agile and Scrum, and I am well-versed in monitoring and alerting tools like the Elastic Stack, Prometheus, and Grafana.
Weitere Kenntnisse
Agentic AI: LangChain, CrewAI, LangGraph, LangSmith, Auto-GPT, BabyAGI, Planning Algorithms, Tool Integration, Memory Management
Large Language Models (LLMs): GPT-4o, Claude 3.5 Sonnet, Gemini, Flan-T5, LLaMA, Gemma, BERT
Generative AI Techniques: LoRA, RLHF, Instruction Fine-Tuning, Prompt Engineering (Few-Shot Prompting, In-Context Learning, Self-Consistency)
Machine Learning (ML): Scikit-learn, PyTorch, Hugging Face
Retrieval Augmented Generation (RAG): Chroma, LangChain
MLOps: MLflow, Docker, Kubernetes, Helm, Kubeflow, CI/CD Pipelines
Cloud Computing (GCP): Vertex AI, BigQuery
DevOps: Terraform, Prometheus, Grafana, Splunk
Agile & Scrum: Project Management, Agile Methodologies
Experimentation & CI/CD: MLflow, Agile/Scrum methodologies
Monitoring & Alerting: Elastic Stack, Prometheus, Grafana
Software Development: Python, Java, Spring Boot, Microservices, REST APIs, Kafka, Graph Databases, Swagger, ReadyAPI, OAuth2
Persönliche Daten
- Englisch (Fließend)
- Deutsch (Grundkenntnisse)
- Urdu (Muttersprache)
- Europäische Union
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