Prathamesh is available for hire
Hire PrathameshPrathamesh Saraf
Verified Expert in Engineering
Artificial Intelligence Engineer and Developer
Bengaluru, Karnataka, India
Toptal member since October 6, 2025
Bio
Prathamesh is an AI engineer with deep expertise in building LLM-powered applications, scalable APIs, and data intelligence systems. With experience spanning research, startups, and open-source projects, Prathamesh bridges advanced machine learning with practical, business-driven solutions.
Portfolio
LG NOVA - New Ventures
Artificial Intelligence (AI), Claude API, Python, Anthropic, FastAPI...
CVS Health
Agentic AI, AI Model Integration, AI Model Training...
TrueFoundry
Python 3, FastAPI, Large Language Models (LLMs), Docker, Agentic AI, Google ADK...
Experience
- FastAPI - 5 years
- Python 3 - 5 years
- AI Agents - 4 years
- Artificial Intelligence (AI) - 4 years
- Large Language Models (LLMs) - 3 years
- Retrieval-augmented Generation (RAG) - 3 years
- Agentic AI - 2 years
- Google ADK - 1 year
Preferred Environment
MacOS, Visual Studio Code (VS Code), Slack
The most amazing...
...thing I've completed is help Fortune 5 enterprise ship production grade GenAI
Work Experience
AI Prompt Engineer with Claude and Multi-Agent Workflow Experience
2026 - 2026
LG NOVA - New Ventures
- Led end-to-end development of an AI course-generation platform, shipping 150+ changes across ~380 files (+53K lines) and 13 releases in 4 months, turning raw PDFs and web pages into complete interactive learning experiences.
- Built an AI learning assistant answering learner questions in real time from course material, returning source-cited answers via a hybrid retrieval engine tuned to 2,000 requests/minute, backed by a feedback-driven evaluation harness.
- Automated the full multimedia pipeline, auto-generating narrated videos, AI-presenter videos, 10 slide formats, and 5 diagram types from source content, cutting course production from days of manual work to minutes.
- Raised content quality and trust with an automated evaluation system scoring every course for factual accuracy and instructional depth, hardened by 30+ tests catching calculation and rendering errors before learners see them.
- Drove cost visibility and organic growth via per-course cost tracking with an admin analytics dashboard plus shareable, socially-optimized course pages with one-click content export.
Technologies: Artificial Intelligence (AI), Claude API, Python, Anthropic, FastAPI, Large Language Models (LLMs), Claude, Next.js, React, Node.js, AI Systems
Applied AI Consultant
2024 - 2026
CVS Health
- Led the development of an organization-wide outbound campaign management system that uses an AI voice agent pipeline for seamless SIP outbound campaigns.
- Partnered with data science and product teams to ensure seamless deployment of AI models within a regulated healthcare environment, maintaining compliance and security.
- Oversaw the development of the generative AI stack, integrating agentic workflows, RAG pipelines, and LLM fine-tuning to enhance analytics and customer engagement at enterprise scale.
- Published a technical article on: Transforming Customer Interactions: Evolving IVR Systems in CVS Health Tech Blog.
- Revamped legacy IVR systems using AI-driven agentic pipelines, improving customer query resolution rate to 95% and reducing average handling time.
- Delivered AI and agentic stack training to product leaders and enterprise teams, while contributing to strategic planning and roadmap execution for production-grade AI systems.
Technologies: Agentic AI, AI Model Integration, AI Model Training, Artificial Intelligence (AI), APIs, Cloud, AI Agents, Natural Language Queries, AI Chatbots, Prompt Engineering, Chatbot Conversation Design, Multi-agent Systems, Generative Artificial Intelligence (GenAI), Python Asyncio, ChatGPT Prompts, Data Science, Evaluation, Gemma API, Llama API, Natural Language Processing (NLP), OpenAI API, Reinforcement Learning from Human Feedback (RLHF), Vector Databases, OpenAI, Claude, API Development, API Integration, Chatbots, Asyncio, Leadership, Data Analysis, MongoDB, AI Data Classification, REST APIs, Webhooks, Model Tuning, Model Context Protocol (MCP), Agentic Frameworks, AI Integration, PDF, Healthtech, Design, Dashboards, Health, Executive Consulting, ChatGPT, OpenAI GPT-4 API, Architecture, Business Analysis, Functional Analysis, Cursor AI, AI Modeling, Software Architecture, TensorFlow, PyTorch, Vertex AI, Technical Project Management, Sentiment Analysis, Anthropic, JSON, Platform as a Service (PaaS), Software Development Lifecycle (SDLC), AI Automation, Automation, Azure, Microsoft Excel, AI Tools, Multimodal Models, Document Processing, Microservices, Deep Learning, Solution Architecture, Workflow, Multimodal GenAI, Local Hosting, Workflow Automation & System Integration, Generative Pre-trained Transformers (GPT), Hugging Face, Open-source LLMs, Firecrawl, AI Assistants, Small Language Models (SLMs), Fine-tuning, Llama 3, LlamaIndex, Mistral AI, Multistage LLM Chains, Database Structure, LoRa, Qwen, Gemini, Prototyping, Semantic Search, vLLM, Data Protection, HIPAA Compliance, RAG Architecture, DeepSeek, Meta Llama, Workflow Automation, Text-to-Speech (TTS), Back-end Development, Pydantic, Agentic RAG Systems, Azure OpenAI Service, Automatic Speech Recognition (ASR), Speech-to-Text (STT), Model Evaluation, RAG Pipelines, Bots, Best Practices, Data Management, Data Architecture, Data Engineering, Data Analytics, Claude API, ChatGPT API, Claude Code, Google Cloud Platform (GCP), AI Copilots, AI Security, Claude Agent SDK, IT Project Management, IT Projects, SQL, AI Architecture, Training, AI Consulting, Conversational Agent, Twilio, Twilio API, AI Voice Agents, Synthetic Data Generation, Hugging Face Transformers, Ollama, Decision Modeling, Agentic AI Systems, Embedding Models, ElevenLabs Solutions, API Design, Slack, Visual Studio Code (VS Code), MacOS, Automations, AI Systems
Senior Software Engineer
2024 - 2026
TrueFoundry
- Led the development of Cognita, an open-source RAG framework that has earned 3,000+ GitHub stars, which is now used by enterprise teams to build context-aware AI systems.
- Worked as a solutions architect for Truefoundry clients as part of the Enterprise Outcome team, such as Merck, Otsuka, Siemens, to ensure the successful delivery of outcomes from a data science perspective.
- Maximized product adoption, ensured a smooth integration of the TrueFoundry product, and closed the customer feedback loop.
Technologies: Python 3, FastAPI, Large Language Models (LLMs), Docker, Agentic AI, Google ADK, LangGraph, LangChain, APIs, AI Model Integration, Vector Data, Machine Learning, AI Agents, Prompt Engineering, Multi-agent Systems, Generative Artificial Intelligence (GenAI), Machine Learning Operations (MLOps), Python Asyncio, Data Science, Evaluation, Gemma API, Llama API, Natural Language Processing (NLP), OpenAI API, Vector Databases, OpenAI, Claude, n8n, API Development, API Integration, Asyncio, Data Analysis, MongoDB, REST APIs, Webhooks, Model Tuning, Agentic Frameworks, AI Integration, PDF, JavaScript, Node.js, ChatGPT, OpenAI GPT-4 API, Architecture, Microsoft Copilot, Cursor AI, AI Modeling, Software Architecture, TensorFlow, PyTorch, Anthropic, Pattern Analysis, JSON, Platform as a Service (PaaS), AI Automation, Automation, PDF Scraping, Vector Search, Microsoft Excel, AI Tools, Multimodal Models, Large Language Model Operations (LLMOps), Microservices, Deep Learning, Solution Architecture, Multimodal GenAI, Amazon SageMaker, Amazon Elastic Container Service (ECS), Gmail, Generative Pre-trained Transformers (GPT), Hugging Face, Open-source LLMs, AI Assistants, Small Language Models (SLMs), Fine-tuning, Llama 3, LlamaIndex, Mistral AI, Multistage LLM Chains, Database Structure, LoRa, Gemini, Prototyping, vLLM, Distributed Systems, Graph Databases, RAG Architecture, DeepSeek, Meta Llama, Workflow Automation, Back-end Development, Technical Leadership, Pydantic, Agentic RAG Systems, Amazon S3 (AWS S3), Amazon Bedrock, Azure OpenAI Service, Model Evaluation, RAG Pipelines, Bots, Best Practices, Data Management, Data Architecture, Data Engineering, Data Analytics, Claude API, Weaviate, ChatGPT API, Claude Code, Google Cloud Platform (GCP), AI Copilots, AI Security, Claude Agent SDK, SQL, Natural Language Understanding (NLU), DevOps, RAG Systems, AI Architecture, Optical Character Recognition (OCR), Training, AI Consulting, Conversational Agent, Synthetic Data Generation, Hugging Face Transformers, Ollama, Decision Modeling, Agentic AI Systems, Embedding Models, ElevenLabs Solutions, API Design, Slack, Visual Studio Code (VS Code), MacOS, Automations, AI Systems
AI Engineer
2025 - 2025
Cogentic Labs Inc.
- Architected and deployed a multi-agent natural language database query system, reaching 70-80% faster response times and 65% cost reduction through intelligent query classification, Redis caching, and zero database load for conversational follow-ups.
- Designed a secure SQL payload generation architecture replacing direct database access, implementing role-based access control, multi-tenant data isolation, and comprehensive validation to prevent SQL injection across the enterprise platform.
- Built a database-agnostic configuration system using YAML schemas, enabling deployment to any PostgreSQL database without code changes, reducing set-up time from days to hours for new environments.
Technologies: JavaScript, Node.js, Next.js, Amazon Web Services (AWS), React, Shadcn, AI Chatbots, AI Assistants, Large Language Models (LLMs), TypeScript, PostgreSQL, Amplitude, REST APIs, OpenAI API, Troubleshooting, Prompt Engineering, Workflow Automation, Back-end Development, Technical Leadership, Web Development, Pydantic, Agentic RAG Systems, Best Practices, Data Management, Data Engineering, Data Analytics, Claude API, ChatGPT API, AI Security, SQL, Natural Language Understanding (NLU), RAG Systems, AI Architecture, AI Consulting, Conversational Agent, Ollama, Decision Modeling, Agentic AI Systems, Embedding Models, ElevenLabs Solutions, API Design, Visual Studio Code (VS Code), MacOS
Founding Engineer | Technical Lead
2021 - 2024
Chatowl
- Spearheaded the design and implementation of the technical and product stack for ChatOwl’s therapeutic sessions, playing a pivotal role in shaping the product roadmap.
- Orchestrated seamless collaboration between multiple teams, ensuring the timely delivery of multiple successful product releases.
- Tackled a diverse array of challenges spanning conversational AI, Databases, back-end development, LLMs, and DevOps.
- Demonstrated strategic thinking, research skills, quick adaptability to emerging technologies, and the ability to devise innovative solutions that yielded both monetary and technical advantages.
Technologies: Conversational AI, Rasa NLU, Rasa.ai, Large Language Models (LLMs), AI Chatbots, Chatbot Conversation Design, Python Asyncio, Data Science, Natural Language Processing (NLP), OpenAI API, Vector Databases, API Development, API Integration, Chatbots, Leadership, Data Analysis, Data Annotation, Data Labeling, MongoDB, AI Data Classification, REST APIs, Architecture, Google Colaboratory (Colab), Technical Project Management, Pattern Analysis, JSON, Django, Deep Learning, Hugging Face, Psychology, Database Structure, Prototyping, Distributed Systems, HIPAA Compliance, Back-end Development, Technical Leadership, Pydantic, Best Practices, Data Analytics, API Design, Visual Studio Code (VS Code), MacOS
Junior Chatbot Developer
2020 - 2021
Saarthi
- Designed, developed, and maintained multilingual text and IVR-based chatbots.
- Worked extensively on RASA and modified its open-source code to set up automated testing for conversations, which improved the testing effort by 50%.
- Set up analytics services for chatbots that help in generating business leads, that help grow business outreach by 20%.
- Containerized and set up a serverless environment for deployment, which saved the cloud cost by 15% compared to a normal VM deployment.
Technologies: Python, FastAPI, Rasa.ai, AI Chatbots, Chatbot Conversation Design, Python Asyncio, Data Science, Natural Language Processing (NLP), API Development, API Integration, Chatbots, Data Analysis, Data Annotation, Data Labeling, REST APIs, JavaScript, Node.js, Web Scraping, Google Colaboratory (Colab), JSON, Django, API Design
Experience
My Adventures with Large Language Models
https://leanpub.com/adventures-with-llmsAuthored a technical book that demystifies how large language models actually work, building up from fundamental blocks all the way to cutting-edge architectures. Unlike resources that lean on theory or implementation alone, it takes a blended, highly visual approach so readers can literally "see" ideas evolve — from vectors to attention, transformers, and efficient training. I owned the entire lifecycle: research, writing, illustration, code implementation, and the design of intuitive explanations aimed at engineers, students, and AI practitioners. The goal was to create one of the most accessible, technically accurate, and practical guides for anyone who wants to understand LLMs from first principles. The book is complete and has earned 50+ organic sales with zero marketing spend, driven entirely by word of mouth and the quality of the material.
MCP Registry & Playground
https://mcps.truefoundry.comBuilt a public-facing catalog and interactive playground for Model Context Protocol (MCP) servers on TrueFoundry's AI Gateway. Users browse the catalog, connect their own accounts (Slack, Gmail, GitHub, and more) via OAuth, and call tools through an LLM-powered chat interface. I built the FastAPI backend and the React (Vite + Tailwind) single-page app, plus a GitOps pipeline where each MCP is declared as YAML in-repo and auto-synced to the gateway via tfy apply — GitHub Actions runs a dry-run on every PR and applies on merge. Scaled the registry to 1,368 MCP servers, each with its own config and display metadata, and added OAuth credential rotation for new tenants and production deployment to TrueFoundry clusters. ~114 commits and ~87K lines over three months.
Setu - UPSC Current Affairs & AI MCQ Platform
https://setu.prathameshsaraf.comBuilt an EdTech platform that converts daily Indian Express and PIB (Press Information Bureau) current-affairs coverage into exam-ready study material for UPSC aspirants. I designed and built the async FastAPI (Python 3.13) backend end to end: resilient scrapers for both sources with row-by-row fallbacks, and a two-stage LLM pipeline that first classifies each article for relevance, then auto-generates subject- and difficulty-tagged MCQs. Added a retry-stashing mechanism so a database failure never wastes an LLM call — stalled jobs drain automatically on the next run. Secured every endpoint with Google SSO and JWT, shipped an admin ops-and-cost dashboard, and built backfill and daily-cron tooling with A/B model comparison to control quality and spend. Clean layered architecture (controller → service → repository) on PostgreSQL, covered by pytest, with a React + TypeScript frontend.
super-hype: Human-in-the-Loop Employee Advocacy Platform
https://github.com/S1LV3RJ1NX/superHypeBuilt solo, end to end. super-hype turns a single company announcement into a wave of genuine, on-voice LinkedIn advocacy from the people who actually built the product — no scraping, no shared logins, no bot-style spam. I designed and shipped the full stack: an async FastAPI API with an ARQ background worker (PostgreSQL + Redis) and a React 18 + TypeScript + Tailwind/shadcn frontend. Two workflows — Amplify (a roster engages one existing post) and Distribute (a distinct on-voice post per participant) — with per-persona AI generation tuned to each teammate's voice, a comment-quality floor, and a hard buzzword ban. Every action runs on each member's own consented account through LinkedIn's official API, with Fernet-encrypted tokens, human-in-the-loop approval via web or a bundled Slack DM, randomized publish pacing with daily caps for authenticity, idempotent publishing, campaign controls (pause/resume/reset), roles, a contribution leaderboard, and an append-only audit trail. ~38 commits and ~40K lines in ~3 weeks.
Yukti – LLM-powered Data Intelligence Platform
Yukti is an enterprise-grade platform that enables organizations to interact naturally with their data. It combines retrieval-augmented generation (RAG), advanced vector search, and LLM-driven reasoning to let teams query unstructured and structured data in plain language and receive precise, contextual insights.
Yukti empowers analysts, business leaders, and operations teams to explore documents, reports, and databases without needing technical skills—accelerating decision-making and improving productivity across enterprises.
Yukti empowers analysts, business leaders, and operations teams to explore documents, reports, and databases without needing technical skills—accelerating decision-making and improving productivity across enterprises.
CARL: Cost-optimized Online Container Placement on VMs Using Adversarial Reinforcement Learning
https://ieeexplore.ieee.org/document/10839070Containerization has become the standard for deploying applications on public clouds, where enterprises may host hundreds of applications on thousands of containers across numerous VMs. Efficiently placing container workloads onto available VM capacities is a cost-critical and computationally challenging problem, often modeled as a multi-dimensional Vector Bin-Packing Problem (VBP).
We proposed CARL, a novel Adversarial Reinforcement Learning (RL) approach for cost-efficient container placement. CARL mimics the behavior of an offline semi-optimal VBP solver (teacher) while automatically learning a reward function that minimizes VM costs and outperforms the teacher’s performance. It requires minimal historical workload traces and remains resilient to distributional shifts during inference.
We evaluated CARL on large-scale workloads derived from Google and Alibaba traces, placing 5,000-10,000 container requests across 2,000-8,000 VMs. CARL achieved approximately 1,900 placement decisions/sec, delivered approximately 16% lower VM costs than state-of-the-art methods, and maintained robustness under varying resource and workload conditions, demonstrating real-time, scalable efficiency for modern cloud orchestration.
We proposed CARL, a novel Adversarial Reinforcement Learning (RL) approach for cost-efficient container placement. CARL mimics the behavior of an offline semi-optimal VBP solver (teacher) while automatically learning a reward function that minimizes VM costs and outperforms the teacher’s performance. It requires minimal historical workload traces and remains resilient to distributional shifts during inference.
We evaluated CARL on large-scale workloads derived from Google and Alibaba traces, placing 5,000-10,000 container requests across 2,000-8,000 VMs. CARL achieved approximately 1,900 placement decisions/sec, delivered approximately 16% lower VM costs than state-of-the-art methods, and maintained robustness under varying resource and workload conditions, demonstrating real-time, scalable efficiency for modern cloud orchestration.
AIME – AI Meeting Intelligence & Analysis Platform
AIME is an AI-powered meeting intelligence platform that records, transcribes, and analyzes sales calls to extract deep insights. It identifies buyer pain points, analyzes personality and sentiment, and generates concise summaries with next-step recommendations.
Leveraging agentic AI workflows, AIME enables sales teams to uncover customer intent, improve communication effectiveness, and close deals faster. The platform’s modular design allows enterprises to customize workflows, integrate CRMs, and scale AI inference seamlessly across teams.
Leveraging agentic AI workflows, AIME enables sales teams to uncover customer intent, improve communication effectiveness, and close deals faster. The platform’s modular design allows enterprises to customize workflows, integrate CRMs, and scale AI inference seamlessly across teams.
Algorithmist | Teaching Channel for DSA
https://www.youtube.com/c/AlgorithmistcoderI helped students learn data structures and algorithms by teaching from first principles and intuition. I designed structured problem-solving frameworks to help students transition from brute-force thinking to optimized solutions using time and space complexity analysis.
Education
2021 - 2024
Master's Degree in Computational and Data Sciences
Indian Institute of Science - Bangalore, India
Certifications
JULY 2026 - PRESENT
Claude Certified Architect - Foundations
Claude
AUGUST 2025 - PRESENT
Building Knowledge Graphs with LLMs
Neo4j
AUGUST 2025 - PRESENT
Build intelligent agents with Agent Development Kit (ADK)
Google Cloud
APRIL 2022 - PRESENT
CodeChef Certified Data Structures and Algorithms (CCDSA) Foundation Level
CodeChef
Skills
Libraries/APIs
API Development, REST APIs, Pydantic, Python Asyncio, Llama API, OpenAI API, Asyncio, Node.js, TensorFlow, PyTorch, Claude API, Twilio API, Hugging Face Transformers, React, Rasa NLU, vLLM, SQLAlchemy, Slack API
Tools
Slack, Claude, ChatGPT, Microsoft Copilot, Claude Code, Docker Compose, DeepSeek, Azure OpenAI Service, Claude Agent SDK, Visual Language Models (VLMs), Rasa.ai, Celery, Grafana, n8n, Microsoft Excel, Amazon SageMaker, Amazon Elastic Container Service (ECS), LaTeX, Draw.io, Shadcn
Languages
Python 3, Python, SQL, JavaScript, TypeScript, C, C++, YAML
Frameworks
LangGraph, Agentic Frameworks, LlamaIndex, Django, Next.js, Alembic, OAuth 2, JSON Web Tokens (JWT), Tailwind CSS
Paradigms
Functional Analysis, Model Context Protocol (MCP), Role-based Access Control (RBAC), Automation, Microservices, Best Practices, Synthetic Data Generation, REST, HIPAA Compliance, DevOps
Platforms
MacOS, Visual Studio Code (VS Code), LiveKit, Docker, Vertex AI, Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Twilio, Ollama, NVIDIA CUDA, Linkedln
Storage
JSON, PostgreSQL, MongoDB, Data Pipelines, Database Structure, Amazon S3 (AWS S3), Neo4j, Databases, Graph Databases
Industry Expertise
Cybersecurity
Other
Artificial Intelligence (AI), FastAPI, Large Language Models (LLMs), Agentic AI, Google ADK, LangChain, Retrieval-augmented Generation (RAG), APIs, AI Model Integration, Conversational AI, AI Model Training, Machine Learning, AI Agents, AI Chatbots, Prompt Engineering, Chatbot Conversation Design, Multi-agent Systems, AI Voice Agents, Generative Artificial Intelligence (GenAI), ChatGPT Prompts, Natural Language Processing (NLP), Vector Databases, OpenAI, API Integration, Chatbots, Leadership, Research, Optical Character Recognition (OCR), Model Tuning, AI Integration, PDF, OpenAI GPT-4 API, Text-to-Speech (TTS), Business Analysis, Cursor AI, Software Architecture, Sentiment Analysis, Anthropic, AI Tools, Document Processing, Large Language Model Operations (LLMOps), Multimodal GenAI, Local Hosting, Generative Pre-trained Transformers (GPT), Hugging Face, Open-source LLMs, AI Assistants, Troubleshooting, Small Language Models (SLMs), Fine-tuning, Llama 3, Gemini, RAG Architecture, Meta Llama, Agentic RAG Systems, Speech-to-Text (STT), RAG Pipelines, ChatGPT API, RAG Systems, AI Architecture, Training, Conversational Agent, Cartesia, Deepgram, Agentic AI Systems, API Design, Reinforcement Learning, Cloud, Voice Chat, Data Structures, Algorithms, Natural Language Queries, Machine Learning Operations (MLOps), Data Science, Evaluation, Gemma API, Reinforcement Learning from Human Feedback (RLHF), Data Analysis, ChromaDB, Data Annotation, Data Labeling, AI Data Classification, Webhooks, Healthtech, Design, Dashboards, Health, Executive Consulting, Architecture, Web Scraping, AI Modeling, Google Colaboratory (Colab), Technical Project Management, Pattern Analysis, Platform as a Service (PaaS), Software Development Lifecycle (SDLC), AI Automation, PDF Scraping, Vector Search, Multimodal Models, FAISS, Deep Learning, Solution Architecture, Workflow, Gmail, Workflow Automation & System Integration, Psychology, Firecrawl, Mistral AI, Multistage LLM Chains, LoRa, Qwen, Prototyping, Semantic Search, Distributed Systems, Data Protection, Workflow Automation, Back-end Development, Technical Leadership, Web Development, Amazon Bedrock, Automatic Speech Recognition (ASR), Model Evaluation, Bots, Data Management, Data Analytics, SaaS, Weaviate, Neural Networks, AI Copilots, IT Project Management, IT Projects, AI Consulting, Decision Modeling, Embedding Models, ElevenLabs Solutions, Automations, AI Systems, Knowledge Graphs, Vector Data, Qdrant, Prometheus, Pinecone, Deep Reinforcement Learning, Generative Adversarial Networks (GANs), Virtual Machines, Actor-critic Methods (A2C, A3C), Visualization, Amplitude, Front-end Development, Data Architecture, Data Engineering, Image Processing, AI Security, Natural Language Understanding (NLU), ARQ, Slackbot, GitOps, GitHub Actions, Context Management, Generative AI Architecture, Multi-agent Orchestration, Production reliability, Tool & MCP Design
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