Experience 9+ years
Visa H-1B
Availability Open for Contract - C2C
Based Denver, CO · Open for relocation
Sr AI / ML Engineer

Aditya Guntupalli

Building production-grade Agentic AI systems.

9+ years engineering end-to-end ML and GenAI solutions. Multi-agent architectures, RAG pipelines, and LLM fine-tuning across AWS, GCP, Azure, and Palantir.

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About

I design and build production-grade AI systems for enterprise teams.

Senior AI/ML & GenAI Engineer with 9+ years across energy, healthcare, finance, and retail.

My expertise spans Agentic AI, RAG, LangGraph, MCP servers, Text-to-SQL, fine-tuned LLMs, MLOps, and cloud-native AI platforms across AWS, GCP, Azure, and Palantir.

Recent work focuses on multi-agent GenAI systems that connect LLMs with enterprise backends: Snowflake, Databricks, APIs, operational data, and cloud services. Built on AWS Bedrock, GCP Vertex AI & ADK, Azure AI, Palantir AI, and modern orchestration patterns, turning complex enterprise data into faster, clearer, more actionable insights.

I focus on the engineering layer that makes AI reliable in the real world:

Where I go deep
  • → Secure system integrations
  • → Scalable data pipelines
  • → Agent orchestration
  • → Measurable accuracy
  • → Latency control
  • → Observability
  • → Guardrails & safety
  • → Continuous improvement

Experience

Where I've shipped. A decade of building.

Lead GenAI Engineer

BPX Energy·Denver, CO

Feb 2025 to Present
  • Designed Agentic RAG pipelines on AWS Bedrock + OpenSearch + Snowflake, reducing query resolution time by 30% for field operators.
  • Developed custom Model Context Protocol (MCP) integrations, accelerating onboarding of new agent capabilities by 40%.
  • Built a multi-agent architecture with a central orchestrator routing to specialized sub-agents, reducing latency by ~35% and improving response accuracy by 25%.
  • Shipped a Text-to-SQL tool wired to Snowflake via Lambda, reducing manual query writing for field engineers by 60%.
  • Deployed production agents on Amazon Bedrock AgentCore with session isolation, episodic memory, OAuth identity, and CloudWatch observability.

AI / ML / GenAI Engineer

Optum·Remote

Jan 2023 to Dec 2024
  • Built and fine-tuned a Llama-3.2 LLM on 50K domain examples with LangChain RAG, cutting operational cost 50% vs. commercial APIs.
  • Fine-tuned ResNet50 on 50K medical images, lifting classification accuracy from 82% → 94% for tumor detection.
  • Reduced false positives by 30% through rigorous precision/recall/F1 evaluation pipelines.
  • Optimized GPU training on EC2 P3/G4 instances, cutting training time by 35% via CUDA + distributed training.
  • Met SLAs of <200ms online inference and 20-min batch prediction windows in production.

AI / ML Engineer

First Citizens Bank·Remote

Jan 2022 to Nov 2022
  • Trained fraud detection models on SageMaker. XGBoost hit 95% AUC with a 20% reduction in false positives.
  • Cut training compute costs 40% using EC2 Spot Instances without sacrificing accuracy.
  • Stood up a centralized SageMaker Feature Store with 99.9% uptime for real-time feature reuse.
  • Deployed SageMaker Model Monitor for drift detection, maintaining 99% reliability in production.

Machine Learning Engineer

L.L.Bean·Remote

Dec 2019 to Nov 2021
  • Built churn prediction models that drove a 15% reduction in customer churn.
  • Shipped a hybrid recommendation system (collaborative + content-based) that lifted product sales by 25%.
  • Improved classification F1 by 12% using Azure ML HyperDrive for hyperparameter tuning.
  • Integrated Azure Cognitive Services for sentiment analysis, lifting feedback classification accuracy by 20%.

Machine Learning Engineer

Aspire Systems·Hyderabad, India

Nov 2016 to Oct 2019
  • Engineered data cleaning, normalization, and feature pipelines on large datasets with Python, SQL, and PySpark.
  • Implemented CI/CD for ML deployment with Git, Docker, and Jenkins, making releases predictable and reproducible.
  • Tuned models via cross-validation and feature selection to hit accuracy and latency targets.

Python Developer

Parallel Wireless·Bangalore, India

Jun 2015 to Nov 2016
  • Automated repetitive workflows in Python, saving 10+ hours/week of manual effort.
  • Built and deployed Flask RESTful services for internal data tooling.
  • Reduced production bugs by 25% with a Pytest-driven testing discipline.

Toolkit

The stack I build with.

Programming Languages

7
Python TypeScript R ReactJS HTML Shell Scripting YAML

Machine Learning / Deep Learning

14
Supervised / Unsupervised ANN CNN NLP Computer Vision GANs LSTM Feature Engineering Transfer Learning Ensemble Models Time Series Recommendation Systems Sentiment Analysis Evaluation Metrics

Frameworks

20
TensorFlow Keras PyTorch Scikit-Learn OpenCV NLTK Pandas Transformers Node.js Flask FastAPI Streamlit Gradio Pickle Pydantic ONNX JAX Anaconda Jupyter Notebook Boto3

Generative AI

18
Fine-tuning LLMs LangChain LangGraph LlamaIndex RAG AI Agents Model Context Protocol (MCP) A2A OpenClaw CrewAI AutoGen Prompt Engineering Hugging Face Phi OpenAI Pinecone Claude Code Cursor

Statistics & Metrics

7
Statistical Analysis Regression Time Series Analysis Confusion Matrix Matplotlib SciPy Probability Theory

MLOps & Data Tools

16
Airflow PySpark Data Build Tool (dbt) MLflow Kubeflow DVC DagsHub Docker Terraform Ansible Git GitHub Actions Jenkins CircleCI CI / CD TensorFlow Serving

Cloud

4 platforms
AWS
Agent Core SageMaker Bedrock Lambda Neptune GNN Lex S3 EC2 IAM CloudWatch AMIs Redshift ML DynamoDB Redis CodeBuild CodeDeploy
GCP
Vertex AI ADK AutoML Cloud Vision API Dialogflow NVIDIA GPUs BigQuery ML VM Instance VPC
Azure
Azure Machine Learning Azure AI & OpenAI Blob Storage Azure Functions Cognitive Services
Palantir
Foundry Ontology

Databases & Data Platforms

8
Snowflake Databricks PostgreSQL MySQL MongoDB Neo4j Graph DB Vector DB Supabase

Monitoring & Logging

6
MLflow Weights & Biases TensorBoard Prometheus Grafana Evidently AI

Credentials

Education & certifications.

Certification

AWS Certified Machine Learning, Specialty

Amazon Web Services

Active

Verify on Credly
Degree

B.Tech, Computer Science

JNTUK · Andhra Pradesh, India

2011 to 2015