Ishank Sharma
Forward Deployed Engineer @ Prentis
About
👋 Hi, I'm Ishank. I am a Forward Deployed Engineer who owns AI deployments end to end inside the customer's environment: discovery, scope, POC, pilot, handoff.A few of my favorite achievements so far: - Built an AI agent that helps you automatically transforms your team’s resolved chat threads into a living FAQ document so no question has to be answered twice reducing repeat questions by 70%.- Designed and launched a Gen AI enabled multi-tenant SaaS platform with a custom query generator, reducing manual effort by 80% (Fast API, SQL, AWS).- Built AI-powered media budget recommendation pipelines, saving $200K/year and reducing processing time by 97% (AWS Lambda, SQL). - Optimized database query performance, improving query latency and QPS by 85% (SQL, PostgreSQL, Docker). I'm passionate about building scalable applications, AI automation, and optimizing workflows. Let's connect and share insights on leveraging technology for innovation!
United States
Los Angeles Metropolitan Area
Computer Software
Healthcare, Customer Discovery, AI Orchestration, Word Embeddings, Retrieval-Augmented Generation (RAG), Graph RAG, Knowledge Graph Reasoning, Gradio, Data Visualization, Explainable AI, Interpretability in AI, React.js, Fast API, PostgreSQL, Docker, Kong API Gateway, Temporal, Back-End Web Development, Google Cloud Platform (GCP), Google ADK
Experience
Forward Deployed Engineer
Prentis
Los Angeles, CA
Owning AI deployments end to end inside the customer's environment: discovery, scope, POC, pilot, handoff in the healthcare insurance industry.
Forward Deployed Engineer
CommerceIQ
Long Beach, CA
Responsible for custom AI deployments
Instructional Student Assistant - (Ethical & Explainable AI)
California State University-Long Beach - College of Business
Long Beach, California, United States
Supported instruction and student learning for Explainable & Ethical AI topics.
Full Stack Engineer
Stealth Startup
- Built and deployed a multi-tenant GenAI-enabled SaaS workflow for analytics using Python, SQL, and AWS, designed for concurrent customer workloads and production reliability. - Developed and benchmarked Text-to-SQL inference pipelines (LLaMA, OpenAI, Gemini), optimizing latency/quality/cost with guardrails (timeouts, fallbacks), caching, and regression tests. - Implemented personalization workflows using semantic embeddings and audience signals to drive targeting/segmentation and message selection; integrated with campaign scheduling and notification pipelines.
Research Assistant (ISA)
California State University-Long Beach - College of Business
Long Beach, California, United States
Research Focus: Neuromarketing - Explored saliency dataset - Generated realtime gaze heat-map on video saliency dataset generated through: https://turkergaze.cs.princeton.edu/
SDE 2
CommerceIQ
Bengaluru, Karnataka, India
AWS-based Recommendation System: Built a media budget recommendation pipeline with AWS Step Functions, SQS, Lambda, and 40 SQL modules, predicting ad spend and saving clients $200K annually while reducing processing time from 1 day to 3 minutes. Cold Start Recommendation: Designed and deployed a synthetic data solution integrating sales and advertising performance data, delivering recommendations with 90% accuracy for clients without historical ad performance. Data Warehouse Migration (Snowflake to Databricks): Orchestrated migration of a budget prediction feature, reducing infrastructure costs by 52% and improving latency by 80% through strategic indexing and broadcast joins
SDE 1
CommerceIQ
Bengaluru
Amazon Advertising Campaign Platform: Engineered a platform for creating and managing Amazon advertising campaigns, boosting user productivity and campaign effectiveness. Automated Strategy Execution Pipeline for Criteo Ads: Developed an automation pipeline to optimize Criteo advertising campaigns, enhancing ad performance and operational efficiency reducing manual campaign operations by 60%.
SDE Intern
CommerceIQ
Bengaluru, Karnataka, India
Multi-Cluster Warehouse Simulation: Simulated high-load multi-cluster environments in Snowflake to evaluate and optimize concurrency performance for dynamic SQL workloads. Performance Monitoring Dashboards: Crafted TP99 performance dashboards with New Relic, doubling transparency into page load times and accelerating bottleneck identification.
Education
California State University, Long Beach
Computer Science
CECS 543 Advanced Software Engineering CECS 551 Adv Artificial Intelligence CECS 528 Adv Analysis of Algorithms CECS 530 Computer Organisation & Architecture CECS 575 Obj Oriented Analysis & Design CECS 524 Adv Topics in Programming Lang CECS 529 Search Engine Technology CECS 546 Fault Tolerant Computing Systems CECS 552 Computer Simulation & Modeling
Ramaiah Institute Of Technology
Computer and Information Science
Ishank Sharma's Contact Information
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