Sridhanya Ganapathi | Generative AI FDE Architect

Profile Summary

Highly skilled Generative AI FDE Architect with 15 years of industry experience, eager to leverage expertise in building generative AI solutions, large language models (LLMs), and machine learning frameworks to drive innovation and solve complex business problems. Strong foundation in Python, Neo4j, LangChain, and cloud platforms like GCP and Vertex AI.

Expertise in building and deploying enterprise-grade AG-UI chatbots, integrating OWL Ontology reasoning agents, intent classification, semantic search, and LLM-powered solutions.
Design and implement LLM-powered agents capable of planning, tool use, and multi-step reasoning.
Apply prompt and workflow design to structure decision-making, reflection, and context-driven actions.
Integrate external tools, APIs, Tavily search, and enterprise data via function calling, routing, and MCP.
Use orchestration frameworks like LangChain and LangGraph to build modular, reliable agent pipelines.
Build agents with memory and state awareness using Qdrant, vector stores, and hybrid retrieval loops.
Evaluate, monitor, and debug agent behavior using tracing, observability tools, and metrics like RAGAs or G-Eval.
Deploy and maintain production-ready multi-agent applications on platforms such as Streamlit.
Mitigate risks in autonomous systems by applying safety guardrails, alignment strategies, and hallucination control.
Developed advanced RAG chatbots with semantic chunking, context reranking, and automatic schema recognition using BigQuery ML.
Translate business workflows into intelligent, interoperable agentic systems for automation and augmentation.

Core Competencies

Generative AI & Machine Learning NLP & Deep Learning Large Language Models (LLMs) Graph Databases (Neo4j) Prompt Engineering RAG (Retrieval-Augmented Generation) Cloud Platforms / Cloud AI Integration Data Science & Feature Engineering Big Data Technologies Statistical Analysis Hypothesis Testing & Regression Analysis Agentic AI with OWL

Technical Skills

Agent Frameworks: LangGraph, Langfuse, LangChain, DeepEval, RAGAs
ML / DL: TensorFlow, PyTorch, Hugging Face, Transfer Learning
Data & Cloud: BigQuery ML, GCP, AWS, Vertex AI, MLflow, Model Garden
Graph & Vector DBs: Neo4j, Qdrant, Weaviate, Milvus, FAISS, AlloyDB
Search & Infra: Elasticsearch, Docker, Kubernetes, Terraform, GitHub Actions
NLP: Python, NLTK, spaCy, Transformers
Big Data: Hadoop, HDFS, Spark, PySpark, Hive

Soft Skills

Thought Leadership
Strategic Thinking
Problem Solving
Team Building & Leadership

Work Experience

Senior Architect | FDE

Publicis Sapient, Bangalore

Dec 2024 – Present

Key Result Areas:

5+ GenAI-powered products built from 0→1 in Healthcare and Retail.
AI architecture, GenAI adoption, and consulting grounded in real execution — moving from pilots to production.
Agentic and GenAI adoption through strategy, innovation, solution architecture, and Responsible AI.
Architected and deployed enterprise chatbots utilizing text embedding search, semantic routing, intent classification, and entity resolution pipelines.
Expedited content generation for a leading healthcare client using LLMs and RAG pipelines; ~70% content reuse from existing materials.
Utilized multimodal LLMs to recommend images corresponding to generated content.
Contributed to a 20% cost reduction by streamlining the content generation process.
Deployed GenAI models — Llava, OpenAI GPT, AWS Bedrock Claude — on AWS using Docker, GitHub Actions, Terraform, and Kubernetes.
Built deterministic evaluators replacing LLM-as-judge with repeatable, rule-based scoring for governance-grade evaluation.
Raised production quality through prompt governance, lifting accuracy 2%–5% and reducing regressions.
Architected agents with memory and state awareness using Qdrant, vector stores, and hybrid retrieval loops.
Leading a team of Data Scientists, driving data-driven solutions for business intelligence and process automation.

Architect

Neustar, Bangalore

Nov 2019 – Nov 2024

Engineered systems for structured data ingestion and relationship extraction using Neo4j.
Implemented RAG-based architecture with strategic chunking and context re-ranking using CometML and Neo4j.
Led development and integration of LLM applications with ranking, fine-tuning, and RAG architecture.
Designed pipelines for automating schema recognition and data engineering using BigQuery ML.
Applied transfer learning to image models (VGG16, ResNet, EfficientNet) using TensorFlow and PyTorch.
Led end-to-end data science: acquisition, preparation, modeling, and deployment.
Implemented ML models: Random Forest, Naive Bayes, SVM, KNN, gradient boosting.
Specialized in NLP: text mining, topic modeling, sentiment analysis, entity recognition.
Delivered scalable AI solutions on GCP and AWS; built data pipelines with Spark, PySpark, Hive, and Elasticsearch.
Optimized models via grid search, randomized search, and K-fold cross-validation using MLflow and Vertex AI.

Principal Engineer

Innoviti Payment Solutions Pvt. Ltd., Bangalore

Apr 2016 – Jun 2016

Product Development Specialist

Ellucian, Bangalore

Dec 2010 – Mar 2016

Education

M.Tech. (Data Science)

BITS Pilani