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I'm Akhila Laxmi Juttu, an AI/ML engineer with 3.5 years of hands-on experience building production-grade machine learning and generative AI systems. I specialize in developing LLM-powered applications, Retrieval-Augmented Generation pipelines, and AI-driven automation workflows for enterprise platforms. I am proficient in model development, transformer fine-tuning, distributed data processing, and ML deployment using Python, PyTorch, LangChain, Spark, and AWS. I focus on building reliable, production-ready AI systems that scale with large-scale data and real-world applications.…I'm Akhila Laxmi Juttu, an AI/ML engineer with 3.5 years of hands-on experience building production-grade machine learning and generative AI systems. I specialize in developing LLM-powered applications, Retrieval-Augmented Generation pipelines, and AI-driven automation workflows for enterprise platforms. I am proficient in model development, transformer fine-tuning, distributed data processing, and ML deployment using Python, PyTorch, LangChain, Spark, and AWS. I focus on building reliable, production-ready AI systems that scale with large-scale data and real-world applications.

Akhila Laxmi Juttu

AI Engineer, AI Developer, Data Scientist, +4

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I'm Akhila Laxmi Juttu, an AI/ML engineer with 3.5 years of hands-on experience building production-grade machine learning and generative AI systems. I specialize in developing LLM-powered applications, Retrieval-Augmented Generation pipelines, and AI-driven automation workflows for enterprise platforms. I am proficient in model development, transformer fine-tuning, distributed data processing, and ML deployment using Python, PyTorch, LangChain, Spark, and AWS. I focus on building reliable, production-ready AI systems that scale with large-scale data and real-world applications.…I'm Akhila Laxmi Juttu, an AI/ML engineer with 3.5 years of hands-on experience building production-grade machine learning and generative AI systems. I specialize in developing LLM-powered applications, Retrieval-Augmented Generation pipelines, and AI-driven automation workflows for enterprise platforms. I am proficient in model development, transformer fine-tuning, distributed data processing, and ML deployment using Python, PyTorch, LangChain, Spark, and AWS. I focus on building reliable, production-ready AI systems that scale with large-scale data and real-world applications.

Available to hire

I’m Akhila Laxmi Juttu, an AI/ML engineer with 3.5 years of hands-on experience building production-grade machine learning and generative AI systems.

I specialize in developing LLM-powered applications, Retrieval-Augmented Generation pipelines, and AI-driven automation workflows for enterprise platforms. I am proficient in model development, transformer fine-tuning, distributed data processing, and ML deployment using Python, PyTorch, LangChain, Spark, and AWS. I focus on building reliable, production-ready AI systems that scale with large-scale data and real-world applications.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Applied AI Engineer at Stripe

April 1, 2025 - Present

Architected an LLM-powered developer copilot within the Stripe Dashboard, translating natural-language prompts into validated payment workflows and API integrations using prompt orchestration and schema-aware structured outputs. Engineered a Retrieval-Augmented Generation (RAG) pipeline across Stripe API documentation and SDK examples, improving developer query accuracy. Developed agent-based automation workflows enabling the assistant to diagnose integration issues by inspecting payment logs, transaction analytics, and fraud telemetry services, reducing debugging time. Built a natural-language analytics interface translating prompts into optimized SQL queries on Snowflake for real-time merchant insights. Established AI evaluation and reliability frameworks with benchmark datasets, hallucination checks, and human-in-the-loop feedback to raise accuracy and reliability. Deployed containerized inference microservices with CI/CD and observability tooling to support 8K+ daily interactions w

AI/ML Engineer at Accenture

January 1, 2022 - August 1, 2024

Programmed enterprise content-generation use cases and performed large-scale data understanding with Python, cleaning and structuring 3M+ knowledge-base documents to create high-quality training datasets for generative AI models. Fine-tuned transformer models using PyTorch on domain-specific enterprise data to improve relevance of generated content. Built reusable model training pipelines with Hugging Face Transformers, implementing tokenization, dataset versioning, and distributed fine-tuning workflows that reduced experimentation cycles by ~40%. Implemented enterprise-scale generative inference workflows using AWS Bedrock and secure API services. Formulated experiment tracking and model lifecycle management with MLflow. Containerized inference services processing 20K+ automated content requests per day. Designed production monitoring and evaluation pipelines tracking generation quality, hallucination rates, and latency with continuous feedback.