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AI/ML Engineer and full-stack developer building production-ready AI applications and agentic workflows—from concept to deployment. Experienced in integrating LLMs, RAG, and AI agents into scalable backend services with reliable monitoring and performance optimization. Skilled in Python, FastAPI, Django, React, TypeScript, SQL, Docker, and cloud platforms (AWS/Azure/GCP). Proven success automating workflows, reducing manual effort, improving accuracy and latency, and delivering robust systems in remote, production environments.…AI/ML Engineer and full-stack developer building production-ready AI applications and agentic workflows—from concept to deployment. Experienced in integrating LLMs, RAG, and AI agents into scalable backend services with reliable monitoring and performance optimization. Skilled in Python, FastAPI, Django, React, TypeScript, SQL, Docker, and cloud platforms (AWS/Azure/GCP). Proven success automating workflows, reducing manual effort, improving accuracy and latency, and delivering robust systems in remote, production environments.

Sravya Nallagantula

AI Engineer, Full Stack Developer, Data Engineer, +2

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AI/ML Engineer and full-stack developer building production-ready AI applications and agentic workflows—from concept to deployment. Experienced in integrating LLMs, RAG, and AI agents into scalable backend services with reliable monitoring and performance optimization. Skilled in Python, FastAPI, Django, React, TypeScript, SQL, Docker, and cloud platforms (AWS/Azure/GCP). Proven success automating workflows, reducing manual effort, improving accuracy and latency, and delivering robust systems in remote, production environments.…AI/ML Engineer and full-stack developer building production-ready AI applications and agentic workflows—from concept to deployment. Experienced in integrating LLMs, RAG, and AI agents into scalable backend services with reliable monitoring and performance optimization. Skilled in Python, FastAPI, Django, React, TypeScript, SQL, Docker, and cloud platforms (AWS/Azure/GCP). Proven success automating workflows, reducing manual effort, improving accuracy and latency, and delivering robust systems in remote, production environments.

Available to hire

AI/ML Engineer and full-stack developer building production-ready AI applications and agentic workflows—from concept to deployment. Experienced in integrating LLMs, RAG, and AI agents into scalable backend services with reliable monitoring and performance optimization.

Skilled in Python, FastAPI, Django, React, TypeScript, SQL, Docker, and cloud platforms (AWS/Azure/GCP). Proven success automating workflows, reducing manual effort, improving accuracy and latency, and delivering robust systems in remote, production environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Language

English

Advanced

Work Experience

AI Engineer at Optum

May 1, 2025 - Present

Built production-ready AI-powered applications using Python, FastAPI, OpenAI APIs, and Docker to automate 100+ weekly workflows with intake, summaries, validations, API actions, and reliable outputs. Improved multi-step workflow accuracy by 15% using LangGraph-based AI agents with routing, tool calling, structured outputs, memory-style context, and feedback loops. Enhanced RAG reliability by 25% using embeddings, metadata enrichment, source validation, output checks, and API integrations across structured and unstructured content. Reduced service latency by 28% by optimizing async FastAPI routes, Redis caching, API payloads, and containerized AWS/Azure services. Achieved p95 latency under 800ms through testing and troubleshooting using Postman, Python scripts, logs, and monitoring checks.

Data Engineer at Accenture

August 1, 2022 - August 1, 2023

Developed scalable data pipelines and validation workflows using SQL, Python, and PySpark to validate mappings, exceptions, completeness, and ML-ready datasets for downstream applications. Tuned Snowflake, SQL, and Spark jobs to improve pipeline performance by 6% via optimized joins, partitions, transformations, and refresh logic. Reduced data quality failures by 25% through multi-source dataset preparation, schema validation, recurring refresh checks, documentation, and stakeholder-ready outputs. Resolved 100+ production issues by owning Airflow monitoring, Jira fixes, AWS publishing, rollback runbooks, deployment checks, and operational logs.

Machine Learning Engineer at Accenture

April 1, 2021 - August 1, 2022

Automated ML evaluation workflows using Python, GitHub Actions, and MLflow to reduce model validation time by 40%, enabling repeatable experiments, benchmark tracking, and release validation. Improved model accuracy and application consistency by integrating TensorFlow, scikit-learn, Pandas, NumPy, SQL, and Python services for preprocessing, model integration, validation, and performance monitoring.