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@jamaljohnson1
Senior AI/ML Engineer specializing in production-ready generative AI and MLOps across cloud platforms.
I am a Senior AI/ML Engineer with 14 years in IT and over 8 years focused on AI, Machine Learning, and Generative AI engineering and architecture, delivering production-grade models across AWS, Azure, and GCP.
I design and implement end-to-end ML lifecycles, MLOps pipelines, RAG systems, prompt engineering, and vector database integrations, and I have deployed scalable solutions using SageMaker, AKS, EKS, Databricks, and Kubernetes while emphasizing observability, security, and governance.
My achievements include architecting Gen AI applications using GPT-family and other LLMs, implementing MLflow-backed model registries and CI/CD for models, optimizing distributed training and inference, and mentoring teams to deliver high-performance, reliable AI systems.
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Work history, roles, and key accomplishments
Tech AI
May 2023 - Present (2 years 6 months)
Designed and deployed end-to-end Generative AI applications and scalable ML architectures on AWS, integrating LLMs, vector DBs (Chroma, Neo4j), and MLOps pipelines to enable real-time inference and CI/CD, improving model lifecycle automation and inference latency.
Onpassive
Sep 2020 - May 2023 (2 years 8 months)
Architected RAG-based systems and real-time ML pipelines using Databricks, PySpark, Azure services and containerized deployments, reducing inference latency and enabling scalable production ML for recommendation and anomaly-detection systems.
SmartBear
Dec 2017 - Sep 2020 (2 years 9 months)
Developed real-time IoT and edge ML solutions, built Spark/Databricks data pipelines and integrated OCR and computer vision workflows to improve anomaly detection and recommendation performance in production environments.
Infosys
May 2014 - Dec 2017 (3 years 7 months)
Built Python frameworks, orchestrated streaming and batch data pipelines on GCP (Dataflow, BigQuery, Cloud Functions) and automated deployments with Terraform and Jenkins to improve data processing efficiency and reduce query times.
Accenture
Dec 2012 - May 2014 (1 year 5 months)
Developed Java/J2EE web services and Spring-based applications, optimized SQL queries and implemented caching to improve application performance and reliability across enterprise projects.
Degrees, certifications, and relevant coursework
Master of Science, Computer Science
Completed a Master of Science in Computer Science, focusing on advanced topics in computing and applied research.
Bachelor of Science, Computer Science
Completed a Bachelor of Science in Computer Science with foundational training in software engineering and data systems.
Software and tools used professionally
Postman
Azure Synapse
Apache Spark
AWS Glue
AWS IAM
Google Cloud Platform
Stackdriver
Google Cloud Storage
GitHub
GitLab
Bitbucket
Kubernetes
Amazon EKS
Azure Kubernetes Service
Jenkins
GitHub Actions
Salesforce
Jupyter
Pandas
PySpark
DB
MySQL
PostgreSQL
MongoDB
Cassandra
Hadoop
HBase
Gmail
Node.js
Django
Spring Framework
Spring MVC
Databricks
Neo4j
OpenCV
Redis
Terraform
PyCharm
Azure DevOps
Jira
jQuery
JavaScript
HTML5
Java
JSON
Clojure
MATLAB
Logstash
AWS CloudTrail
Azure Machine Learning
TensorFlow
PyTorch
MLflow
scikit-learn
Keras
Kubeflow
NLTK
Kafka
FastAPI
Grafana
Kibana
Prometheus
Azure Monitor
Ubuntu
Linux
macOS
Windows
Google App Engine
Gemini
gRPC
Elasticsearch
Milvus
Ansible
AWS Lambda
Serverless
Google Cloud Functions
Azure Functions
Azure SQL Database
pytest
Robot Framework
OAuth2
sso
Airflow
Apache Beam
Time Analytics
Mapped
CUDA
SQL
Azure Cosmos DB
XGBoost
Hugging Face
LightGBM
Amazon ECR
LangChain
LlamaIndex
ChromaDB
Polars
Pinecone
Delta Lake
Azure Logic Apps
CodeQL
Cosmos
Bash
Transform
pgvector
Modal
Enhance
Faiss
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