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AI Engineer with 1+ years in Generative AI, Cloud & Machine Learning.
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Anushka Awasthi is a highly skilled AI/ML Engineer with 1.4 years of experience, specializing in Generative AI, Cloud platforms, and Machine Learning. Her expertise spans developing and deploying RAG-based chatbots, voice AI solutions, and designing Snowflake Cortex agents. She is proficient in a wide array of languages, developer tools, databases, and frameworks, with a strong focus on AWS, Python, and AI/ML orchestration. Her project portfolio demonstrates her ability to build innovative, real-time AI solutions for various sectors.
UIET CSJM University
Bachelor of Technology
August 1, 2020 – June 30, 2024
Shellkode Private Limited
AI/ML Engineer
February 1, 2025 – Present
Bengaluru, Karnataka, India
Arista Networks
Network Engineer Intern
July 1, 2024 – October 1, 2024
Pune, Maharashtra, India
SmartEvent AI Saathi
November 1, 2025 – June 30, 2026
• Developed a real-time, voice-first event planning platform using FastAPI, Agora Conversational AI Engine, and Groq Llama 3.1 to enable natural, low-latency human-AI conversations for event queries and planning. • Implemented intelligent function-calling workflows for smart venue/vendor recommendations, city-specific budget estimation, and automated invitation sending to invitee lists with customizable HTML templates. • Designed a scalable AI-driven planning ecosystem integrating ARES ASR, ElevenLabs TTS, secure RTC token authentication, and a multi-layer conversation auto-save mechanism with webhooks and background monitoring.
View ProjectEnterprise Multi-Domain Voice AI Platform
September 1, 2025 – June 30, 2026
• Designed a modular conversational agent using AWS Bedrock and RAG for domain-specific reasoning (Healthcare/Fintech), integrating seamlessly with IVR platforms like Ozontel and Exotel. • Implemented a low-latency Speech-to-Speech pipeline via LiveKit and Nova Sonic, and Sarvam AI and Whisper for accurate transcription and ElevenLabs for human-like response generation. • Automated Tier-1 support for thousands of daily users, resolving repetitive queries without human intervention and significantly reducing operational overhead for enterprise clients by 70%.
Multi-Agent RAG Orchestration System
April 1, 2025 – June 30, 2026
• Architected a scalable multi-agent framework using AWS Bedrock Agents, featuring a Master Agent that intelligently classifies user intent and routes queries to specialized sub-agents for distinct workflows. • Engineered a precision Retrieval-Augmented Generation (RAG) system using AWS OpenSearch Serverless as the vector store for Knowledge Bases, ensuring accurate context retrieval for complex queries. • Deployed dynamic business logic via AWS Lambda functions triggers for sub-agents and hosted the core backend services on AWS EC2 to ensure high availability and performance.
Scaling Serverless Architecture - AWS
AWS
November 1, 2025 – Present
API Gateway for Serverless Application - AWS
AWS
November 1, 2025 – Present
Generative AI Practitioner - AWS
AWS
November 1, 2025 – Present
Natural Language Processing
Infosys Springboard
January 1, 2024 – Present
Introduction to Front End & Back End Development
Coursera
July 1, 2023 – Present
Cultural Fit Analysis
The candidate's involvement in multiple hackathons and coding challenges, along with extra-curricular activities like teaching and fundraising, indicates a proactive, community-oriented, and continuous learning mindset. The diversity of projects (event planning, enterprise voice AI, multi-agent RAG) and application across different sectors (healthcare, banking, lending, computer vision) demonstrates adaptability and a broad interest in applying AI solutions, which aligns well with a dynamic and innovative work culture.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong ability to design and implement complex AI systems, suggesting good problem-solving and architectural thinking. The experience in automating Tier-1 support and reducing operational overhead points to a results-oriented approach. Participation in hackathons and coding platforms suggests a proactive and collaborative attitude. However, without direct assessment data on communication or teamwork, these are inferences.