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TEJA GOPAL REDDY VAKA

Founding AI Engineer • Wichita, Kansas • v*********@gmail.com • +12******947 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

AI Engineer with 6+ years of experience designing, deploying, and operationalizing production ML and LLM systems across fintech, healthcare, and consumer mobile products. Proven track record reducing GPU inference costs by 33%, cutting support ticket turnaround by 87%, and shipping LLM-backed features used by 10k+ daily users. Seeking to apply production-grade MLOps, LLM safety, and end-to-end AI product skills at a fast-moving startup.

Technical Skills

Programming Languages: Python,Bash
Frameworks and Libraries: PyTorch,TensorFlow,Hugging Face,LangChain,FastAPI
Databases: Snowflake,PostgreSQL,SQL
Cloud and DevOps: Docker,CI,CD,AWS EC2,AWS S3,AWS Lambda,AWS Glue,AWS ECS Fargate,AWS Kinesis,GCP BigQuery,GCP Dataflow,CloudWatch
Data and Analytics: LoRA fine-tuning,ONNX,Retrieval-Augmented Generation,Apache Spark,PySpark,Kafka,Databricks
NLP and Generative AI: GPT-4,Gemini,BERT,T5,LangGraph,LlamaIndex,Prompt engineering
Computer Vision: Groq Llama 3.2 Vision,Multi-pass detection pipelines,Confidence scoring
MLOps and Infrastructure: Apache Airflow,AWS SageMaker,AWS Bedrock,Model monitoring,Drift detection
Mobile and Frontend: React Native,Firebase Auth,Firestore,Firebase Storage,Firebase Analytics,Zustand

Work Experience

Rivulet
Remote
Founding AI Engineer
Jan 2026 – Present
Built a consumer mobile product (iOS/Android) combining household management and AI features; owned mobile frontend, backend APIs, and AI systems as the sole AI engineer.
Tech Stack: React Native, Firebase Firestore, Firebase Analytics, Firestore transactions, Gemini Flash Lite, Groq Llama 3.2 Vision
  • Built and launched a cross-platform React Native app spanning four AI-powered modules (Care, Things, Family, Journal); owned frontend, backend APIs, and cloud infrastructure end-to-end as the sole AI Engineer.
  • Architected Ask Rivulet conversational assistant using Gemini Flash Lite, aggregating context across modules with parallel Firestore queries and guardrails that prompt clarifying questions to prevent hallucinations.
  • Designed a multi-step AI vision scanner using Groq Llama 3.2 Vision with a dual-pass self-review loop and atomic Firestore writes to ensure consistent multi-step scan sessions and reduce missed/occluded items.
  • Researched household cognitive labor (Daminger framework) and iterated UX to introduce proactive nudges and shared cognitive-load visibility based on private beta user feedback.
  • Instrumented Firebase Analytics and event tracking to establish baseline engagement, reached 23 monthly active users in private beta, and created a retention-first product roadmap.
  • Implemented production backend patterns (Firestore rules, Cloud Functions, CI/CD pipelines and monitoring) to ensure app reliability and faster iteration during early launch.
Empower Financial Services
Frisco, TX
AI Engineer
Jan 2023 – Jan 2026
Worked in fintech, building NLP and LLM-backed features for customer support and product experiences; focused on model deployment, cost optimization, and data reliability.
Tech Stack: BERT, LoRA, ONNX, Apache Airflow, CloudWatch, Snowflake, AWS S3, TensorFlow
  • Built and deployed a LoRA-optimized BERT classifier and summarizer for customer intent routing, improving F1 from 0.76 to 0.89 and increasing CSAT by 15% through automated routing.
  • Reduced GPU inference costs by 33% via ONNX export and INT8 quantization, enabling the system to scale to 5x query volume within budget constraints.
  • Rebuilt model deployment pipelines in Airflow with automated rollback hooks, reducing model release cycle from 3 days to 4 hours and enabling safer, faster releases.
  • Implemented statistical drift detection using KS test and PSI with CloudWatch-triggered rollbacks and a monthly retraining loop to maintain SLA-aligned model performance.
  • Led a 5TB migration from S3 to Snowflake to centralize transactional data, which decreased support ticket turnaround from 4 hours to 30 minutes (87% reduction).
  • Delivered an LLM-backed feature serving 10,000+ daily active users; managed AI backend APIs (TensorFlow/BERT) and mentored a junior scientist through deployment and monitoring.
Advithri Technologies LLC
Frisco, TX
Data Engineer
May 2022 – Dec 2022
Delivered data engineering and analytics solutions for enterprise clients using AWS-managed services and real-time pipelines; focused on ingestion reliability and dashboarding.
Tech Stack: AWS Glue, AWS Step Functions, AWS Kinesis, PySpark, pandas, Amazon QuickSight
  • Designed ingestion pipelines using AWS Glue to onboard diverse client feeds and built REST API endpoints for external data producers to standardize data collection.
  • Added retry and circuit-breaker logic across ingestion pipelines to improve availability and reduce downstream pipeline failures.
  • Implemented PySpark and pandas transformation logic to normalize and validate feeds, reducing data processing errors by 15% and enabling real-time analytics across 20+ client systems.
  • Built auto-refreshing KPI dashboards in Amazon QuickSight, cutting manual reporting cycles for Fortune 500 clients and improving stakeholder visibility.
  • Maintained SLA-bound ETL workflows using AWS Step Functions and Kinesis, processing millions of records daily with consistent throughput.
  • Instrumented logging and operational metrics for ingestion jobs to improve incident response and support SLA-driven uptime targets.
Sooth.Al
Wichita, KS
Research Assistant
Sep 2021 – Feb 2022
Supported an AI Q&A platform by curating training data and fine-tuning transformer models to improve contextual responses.
Tech Stack: BERT, Transfer learning, Dataset curation
  • Curated and validated a dataset of 2,000+ question-answer pairs with manual accuracy checks to create a high-quality ground truth for model training.
  • Fine-tuned a BERT-based transformer via transfer learning on the curated dataset, improving contextual understanding and response relevance for the platform's Q&A system.
Ctrl - IT Inc
Hyderabad, India
Data Engineer
Aug 2019 – Feb 2021
Worked on healthcare data engineering projects ingesting clinical/administrative records from multiple facilities into GCP analytics platforms for reporting and compliance.
Tech Stack: GCP Dataflow, Cloud Composer, BigQuery, KS test, k-anonymity, Tokenization
  • Built ETL pipelines using Google Cloud Dataflow and orchestrated workflows with Cloud Composer to ingest healthcare records from 100+ medical facilities for near-real-time analytics.
  • Processed and transformed 10M+ patient records into a BigQuery warehouse, streamlining reporting and reducing query latency for downstream analytics.
  • Optimized BigQuery schemas, partitioning, and clustering to decrease query latency and improve report generation times for clinical dashboards.
  • Implemented data quality checks (KS test, z-score) to detect anomalies and reduce source data errors by 15%.
  • Developed anonymization and tokenization workflows applying k-anonymity to protect patient privacy and maintain compliance with data-protection requirements.
  • Automated ingestion monitoring and alerting to ensure SLA compliance and rapid incident response for data delivery to analytics teams.

Projects

RetireIQ: AI-Powered Retirement Planning Assistant
Tools Used: RAG pipelines, FAISS, GPT-4o-mini, pgvector, FastAPI, AWS Lambda, S3, CloudWatch
  • Built a greenfield RAG pipeline with 3-tier hybrid retrieval (FAISS → cosine → keyword fallback) using GPT-4o-mini to ground retirement advice in IRS and SSA documents with traceable citations across Member and Advisor modes.
  • Implemented an intent router with prompt-injection detection and financial compliance guardrails that enforce safe fallbacks and disclaimer-injected outputs to prevent misaligned LLM responses.
  • Optimized inference cost to ~$0.0005 per query using structured JSON outputs validated by Pydantic, JSONL interaction logging, and a production migration path across FastAPI, AWS Lambda, pgvector, S3, and CloudWatch.

Education

Wichita State University
Master of Science, Computer and Information Sciences • Wichita, KS • Aug 2021 – Dec 2022
SRM University
Bachelor of Technology, Information Technology • Chennai, India • May 2015 – May 2019

Certifications

Building Reliable Agents — LangChain • June 2026
AI Agents Fundamentals — Hugging Face • June 2025
Databricks Accredited Generative AI Fundamentals — Databricks • Feb 2025
Fundamentals Of MCP — Hugging Face • Dec 2024

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