Senior Python AI/ML Engineer

GENIUS M.

Senior Python AI/ML Engineer

Work Authorization: EAD

Open to relocation anywhere in the US

New York, New York 201-***-**** **************@*****.***

LinkedIn: https://linkedin.com/in/geniusmachado

PROFESSIONAL SUMMARY

Senior Python Full Stack & AI Engineer with 6+ years of experience designing and delivering cloud-native applications across Healthcare, Banking, and Retail domains. Expertise in Python, FastAPI, Django, Microservices, AWS, Azure, Generative AI, OpenAI APIs, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), and Machine Learning. Proven success in leading enterprise application modernization, AI platform development, REST API architecture, cloud transformation, and scalable data engineering solutions while driving technical leadership, operational efficiency, and business innovation.

TECHNICAL SKILLS:

Programming Languages: Python, Golang, Java, JavaScript (ES6+), SQL, PL/SQL, C++, C

Backend Frameworks & APIs: Django, Django REST Framework (DRF), FastAPI, Flask, Celery,

Pyramid, RESTful APIs, GraphQL, gRPC

Generative AI & Machine Learning: OpenAI API, Azure OpenAI, Hugging Face Transformers, LangChain,

LangGraph, Retrieval-Augmented Generation (RAG), Prompt Engineering, LLMs, NLP, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, SciPy, Matplotlib

Cloud Platforms: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform

(GCP)

AWS Services: EC2, S3, Lambda, RDS, IAM, API Gateway, CloudWatch,

CloudFormation, Glue, Athena, Redshift, EMR, Kinesis, DynamoDB, SNS, SQS, EKS

Databases: Snowflake, PostgreSQL, MySQL, Oracle, SQL Server, MongoDB,

Cassandra, Redis, DynamoDB, SQLite

Data Engineering & Big Data: PySpark, Spark SQL, Hadoop, Dataiku, ETL/ELT, Informatica, Oracle

Data Integrator (ODI), Azure Data Factory (ADF)

Frontend: React.js, Angular, HTML5, CSS3, Bootstrap, JavaScript, jQuery, AJAX

DevOps & Infrastructure: Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, Ansible,

Maven, Gradle

Version Control: Git, GitHub, Bitbucket, SVN

Messaging & Integration: Apache Kafka, RabbitMQ, REST APIs, SOAP, Apache Camel, Spring

Integration

Testing: PyTest, Selenium, Postman, Swagger/OpenAPI, JUnit, TestNG

Monitoring & Observability: Datadog, Prometheus, Grafana, ELK Stack, New Relic

Development Tools: PyCharm, VS Code, Jupyter Notebook, Eclipse

Operating Systems: Linux (Ubuntu, CentOS, RHEL), Windows

Methodologies: Agile (Scrum), SDLC, Test-Driven Development (TDD), Microservices

Architecture, CI/CD

PROFESSIONAL EXPERIENCE

Client: United health group-Minnetonka, MN April 2023 – Present

Role: Senior Python AI/ML Engineer

Responsibilities:

Owned the end-to-end delivery of enterprise healthcare modernization initiatives by architecting cloud-native Python microservices with FastAPI and Django, reducing deployment time by 60%, improving application availability to 99.9%, and supporting millions of healthcare transactions annually.

Led development of enterprise healthcare platform processing 12M+ patient records, reducing reporting latency by 45%.

Owned the architecture and implementation of an enterprise Generative AI platform using OpenAI APIs, LangChain, LangGraph, Hugging Face, and RAG, reducing document search time by 80%, automating knowledge retrieval for 5,000+ users, and significantly improving operational efficiency.

Directed the design and delivery of enterprise API integration platforms, developing secure, high-performance REST services that connected healthcare applications, CRM systems, and third-party enterprise platforms while ensuring scalability, reliability, and interoperability.

Led a large-scale legacy modernization program by transforming monolithic healthcare applications into cloud-native microservices using FastAPI, Docker, Kubernetes, and AWS, significantly improving deployment agility, maintainability, scalability, and operational resilience.

Owned the delivery of an enterprise predictive analytics platform using Python, PySpark, Azure Machine Learning, and Dataiku, enabling intelligent healthcare decision support through scalable machine learning models, predictive forecasting, and advanced analytics.

Established secure cloud-native AWS infrastructure and enterprise CI/CD engineering standards using EC2, Lambda, S3, RDS, IAM, CloudFormation, Docker, Kubernetes, Terraform, Jenkins, and Git, delivering automated, scalable, and highly reliable application deployment environments.

Provided technical leadership by partnering with enterprise architects, product leadership, DevOps teams, and business stakeholders to define technical strategy, mentor engineers, establish engineering best practices, and successfully deliver enterprise AI and cloud transformation initiatives.

Environment: Python, Django, FastAPI, Flask, REST APIs, AWS, Snowflake, PySpark, Dataiku, OpenAI APIs, Hugging Face, LangChain, LangGraph, RAG, Docker, Kubernetes, Ansible, Terraform, Oracle PL/SQL, React, Angular, PostgreSQL, Azure, Git, Jenkins, Selenium, CI/CD, Agile, TDD.

Client: Bank of America – Charlotte, NC Feb 2021 - March 2023

Role: Python AI/ML Engineer

Responsibilities:

Owned the end-to-end architecture and delivery of enterprise banking application platforms using Python, Django, FastAPI, Flask, and microservices, enabling secure, scalable, and high-performance financial services supporting mission-critical banking operations.

Led the development of an enterprise financial data platform using AWS Glue, Redshift, Snowflake, Amazon S3, and Python, establishing scalable ETL pipelines that transformed high-volume banking data into trusted analytics-ready assets for enterprise reporting and business intelligence.

Owned the architecture and implementation of AI-powered document intelligence platforms leveraging OpenAI APIs, Hugging Face, OCR, NLP, and Machine Learning, automating document processing, improving information extraction, and streamlining enterprise banking workflows.

Led the delivery of enterprise fraud detection and predictive analytics platforms using Python and Machine Learning, enabling intelligent anomaly detection, risk assessment, and data-driven decision-making across banking operations.

Owned the design and implementation of enterprise API integration platforms using Python and Golang, delivering secure, scalable RESTful services that integrated core banking systems with enterprise applications and third-party platforms.

Led enterprise cloud modernization by architecting secure AWS infrastructure using Terraform, CloudFormation, Docker, Kubernetes, IAM, KMS, VPC, Lambda, and API Gateway, establishing scalable, compliant, and highly automated cloud platforms that supported secure enterprise application delivery.

Established enterprise DevOps, CI/CD, and observability platforms using Jenkins, GitHub Actions, Docker, Amazon CloudWatch, Datadog, and Prometheus, improving deployment automation, platform reliability, application performance, operational visibility, and engineering productivity across enterprise banking systems.

Environment: Python, Django, Flask, FastAPI, REST APIs, AWS (EC2, S3, Lambda, Glue, Redshift, CloudWatch, IAM, API Gateway), Snowflake, PySpark, OpenAI APIs, Hugging Face, OCR, NLP, Terraform, CloudFormation, Docker, Kubernetes, Jenkins, GitHub Actions, Golang, Oracle PL/SQL, Datadog, Prometheus, Git, Agile, DevOps.

Client: Best buy-Minneapolis, MN Jan 2020 – Nov 2020

Role: Python Developer

Owned the design and development of enterprise retail application platforms using Python, Django, Flask, and RESTful APIs, delivering scalable backend services that supported mission-critical retail operations and business applications.

Led the development of an enterprise retail data platform using Python, PySpark, Pandas, and ETL frameworks, enabling scalable data ingestion, transformation, and analytics for business intelligence and operational reporting.

Owned the architecture and implementation of AI-powered automation platforms using OpenAI APIs, Hugging Face, LangChain, LangGraph, and Retrieval-Augmented Generation (RAG), delivering intelligent search, document intelligence, and customer support automation solutions.

Owned the design and delivery of enterprise retail applications by developing secure RESTful APIs, scalable backend services, and responsive web applications using Django, Flask, SQLAlchemy, React.js, and Angular, enabling seamless integration between enterprise systems and delivering high-performance user experiences.

Established containerized application delivery and enterprise CI/CD pipelines using Docker, Kubernetes, Jenkins, and GitLab CI, improving deployment automation, release reliability, and operational scalability across development environments.

Optimized enterprise data platforms and backend services using PySpark, PostgreSQL, MongoDB, Cassandra, Redis, MySQL, asynchronous processing, workflow automation, caching, and database optimization, improving application scalability, performance, reliability, and analytics efficiency across retail operations.

Collaborated with cross-functional teams to deliver enterprise retail solutions while implementing monitoring and observability platforms using Grafana, Prometheus, Stackdriver, and Power BI, and contributing to RFID, IoT, and analytics integration initiatives that improved operational visibility, inventory management, and business efficiency.

Environment: Python, Django, Flask, FastAPI, REST APIs, React.js, Angular, JavaScript, HTML5, CSS3, Bootstrap, PySpark, Pandas, OpenAI APIs, Hugging Face, LangChain, LangGraph, RAG, NLP, Docker, Kubernetes, Jenkins, GitLab CI, GCP, PostgreSQL, MySQL, MongoDB, Cassandra, Redis, Power BI, Grafana, Prometheus, Stackdriver, Git, Agile, ETL.

Education

Master of Science in Computer Science (Jan 2022 – Dec 2023)

Pace University

Bachelor of Engineering in Computer Engineering

St. Francis Institute of Technology

Bachelor of Applied Science in Artificial Intelligence

Harrisburg University of Science & Technology

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