Headline

AI Engineer | LLMs · RAG · MLOps · Kubernetes | LangChain · LangGraph · Generative AI | 8 Yrs Enterprise AI | Open to Remote

About

Senior AI/ML Engineer with 8+ years designing and deploying scalable, production-grade AI systems in enterprise environments. I specialise in: - Generative AI & LLMs — RAG architectures, prompt engineering, hallucination reduction, agentic workflows (LangChain, LangGraph) - MLOps & ML Platform — Kubernetes-native orchestration, MLflow, CI/CD pipelines, model monitoring, distributed training - Cloud Infrastructure — GCP (Vertex AI, BigQuery), AWS, Azure (AKS), Terraform, Docker - Data Engineering — Kafka, PostgreSQL, Redis, FastAPI, Python Some things I've shipped: - Reduced cloud compute costs by 60% (~$240K/year saved) at a platform serving 100+ global retailers - Cut ML deployment time by 60% through standardised CI/CD & model versioning - Reduced LLM hallucinations by 35% via prompt versioning & evaluation workflows - Shrunk financial reconciliation cycles by 95% (2 days → minutes) for 1,000+ enterprise customers Currently building AI-native agentic products at the intersection of ML and autonomous systems. Open to fully remote roles globally — ML Engineer, AI Engineer, MLOps Engineer, ML Platform Engineer. 📫 raunaq.soni@gmail.com 🔗 github.com/raunaqness

Location

Bengaluru

AI stack

claude code

cursor

langchain

langgraph

langsmith

Work experience

Independent AI Engineer | Agentic Systems at Network School, Apr 2026 - Present · 5 mos, Remote, Building AI-native products at the intersection of Machine Learning and autonomous agent systems. As an independent software engineer, I design and ship production-grade AI applications — focusing on: - AI Agents and multi-step agentic workflows - Applied ML systems beyond prototype stage - End-to-end architecture (model → orchestration → infra → deployment) - Automation systems that reduce operational overhead Currently a Resident at Network School — a frontier community founded by Balaji Srinivasan (former CTO, Coinbase; former a16z GP), focused on reimagining startup societies and venture ecosystems. Actively exploring early-stage AI opportunities and open to EIR roles or joining as a technical co-founder / founding engineer in ambitious AI-first startups.

Machine Learning Engineer at Aptos Retail, Feb 2023 - Mar 2026 · 3 yrs 2 mos, Project: Unified Commerce Platform - Built backend control services for managing ML jobs on Kubernetes, improving flexibility and reliability in job orchestration. - Designed cloud-native data pipelines using Python and BigQuery for efficient and maintainable batch processing. - Modernized monolithic systems into modular components to enhance scalability and maintainability. Tech stack: Python, Django, Google Cloud Platform, SQL, Docker, Kubernetes, Redis, Terraform, BigQuery Project: Internal LLM-Powered Support Chatbot - Built an end-to-end AI chatbot using large language models to assist users of a retail analytics dashboard. - Integrated internal documentation and metadata to provide context-aware responses using RAG techniques. - Deployed the system using MLOps workflows for efficient experimentation and scalability. Tech stack: Python, FastAPI, LangChain, LangGraph, Vertex AI, VectorDB, Prompt Engineering, Docker, MLOps

Senior Software Engineer at Turing.com, Jun 2022 - Feb 2023 · 9 mos, Palo Alto, California, United States, Project: ML Deployment Platform - Built ML pipelines for data ingestion, training, and automated deployment using Airflow. - Implemented standardized MLOps practices to streamline the end-to-end ML lifecycle. Tech stack: Python, Django, Airflow, Google Cloud Platform, Docker, MLOps

Senior Software Engineer at ClickPost, Jul 2018 - Jun 2022 · 4 yrs, Greater Bengaluru Area, Project: Video Analytics Platform - Built containerized video processing pipelines for retail environments using edge devices and real-time analytics. - Developed a Kafka-based architecture for scalable, streaming computer vision workloads. Tech stack: Python, OpenCV, Kafka, Docker, Computer Vision

Data Scientist at Anheuser-Busch InBev, Jun 2017 - Sep 2017 · 4 mos, Bengaluru Area, India, As a Data Science Intern with decent Software Development skills, I worked across multiple teams on the following projects : - Build a custom Feedback Survey form using Django to collect customer data of their Beer preferences for Sales and Marketing - Analysed customer purchase data to find key insights on which brands to Marketing based on different Geographies - Build a web Dashboard with Python and d3.js for visualising reports data gathered from different teams. Stack: Python, Django, d3.js, R, Rstudio.

Education

Bachelor of Technology (B.Tech.), Computer Science, Guru Gobind Singh Indraprastha University

Scaler

Public links

github: https://github.com/raunaqness

medium: https://medium.com/@raunaqness