Takshit Mathur
@takshitmathur
Senior AI engineer specializing in production ML automation and orchestration.
What I'm looking for
I am a senior AI engineer focused on building production-grade ML and automation systems for enterprise verticals such as insurance, compliance, and healthcare. I design and deploy Python-based pipelines, LLM fine-tuning workflows, and vector-search retrieval systems that scale.
My work includes architecting event-driven, serverless automation using AWS services (SageMaker, Bedrock, Lambda, Step Functions) and optimizing model training via LoRA workflows to cut costs while preserving performance. I have delivered high-throughput systems processing hundreds of thousands of documents and images monthly.
I lead cross-functional engineering efforts to build multi-agent orchestration, real-time VoiceAI pipelines, and distributed microservice backends using FastAPI, Celery, Docker, and Terraform. I emphasize reliability, cost optimization, and measurable accuracy improvements in production ML systems.
I bring strong experience in vector databases, RAG architectures, prompt engineering, and automated evaluation frameworks, and I seek to apply this expertise to deliver scalable AI automation that drives business outcomes.
Experience
Work history, roles, and key accomplishments
Sr. AI Engineer
Alight Solutions
Jan 2025 - Dec 2025 (11 months)
Spearheaded an AI automation team building Python-based document workflow systems for Insurance, Compliance, and Healthcare, deploying production pipelines processing 100K+ documents monthly and improving domain task accuracy to 92% using RAG and vector embeddings.
Sr. AI Developer
Heady
Nov 2024 - Dec 2024 (1 month)
Built AI-powered automation workflows and a Python + FastAPI backend with Celery task orchestration for UGC ad generation, achieving 99.9% uptime and automated multi-modal content generation pipelines.
AI Consultant
CloserX.ai
Jun 2024 - Oct 2024 (4 months)
Led development of a 0-to-1 VoiceAI product using LiveKit and WebRTC, architecting real-time STT-LLM-TTS pipelines with sub-200ms latency and reducing infrastructure costs by 40% via hybrid serverless and container deployments.
AI Lead Designer
Enhancor.ai
Mar 2024 - Jun 2024 (3 months)
Architected serverless GPU infrastructure and Python automation for ComfyUI workflows on RunPod, enabling generation pipelines that processed 500K+ images monthly and supported ~$50K MRR while reducing generation time by 65%.
Developed automated RAG backends and vector search infrastructure processing 10K+ documents with 95% retrieval accuracy, engineered Python/PySpark ETL and streaming pipelines on Databricks and Kafka, and reduced query latency by 60% through index optimizations.
Education
Degrees, certifications, and relevant coursework
Thapar Institute of Engineering & Technology
Bachelor of Engineering, Engineering
2016 - 2020
Completed a Bachelor of Engineering at Thapar Institute of Engineering & Technology with a technical curriculum from June 2016 to June 2020.
Tech stack
Software and tools used professionally
AWS Step Functions
Kubernetes
PySpark
dbt
MySQL
PostgreSQL
MongoDB
Gmail
Node.js
Django
Databricks
Redis
Terraform
JavaScript
TensorFlow
PyTorch
Kafka
FastAPI
Milvus
AWS Lambda
Serverless
Azure Functions
WebRTC
Zapier
Airflow
s3-lambda
CUDA
SQL
Clickhouse
Qdrant
LangChain
ChromaDB
AutoGen
Pinecone
CrewAI
LiveKit
RunPod
N8N
Modal
Faiss
LangGraph
Make
ComfyUI
Task
Availability
Location
Authorized to work in
Job categories
Skills
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