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Available for AI Engineering opportunities

Naveed Asghar

I build production-grade AI systems powered by LLMs, specializing in RAG pipelines, AI agents, and scalable backend architectures that deliver real-world impact.

California, United States
Building AI Systems
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LLMRAGGenerative AIAI AgentsPrompt EngineeringVector DatabasesEmbeddingsPythonFastAPINode.js.NETAWSDockerMicroservicesCI/CD
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About Me

Senior AI Engineer

Senior AI Engineer with 6+ years of experience building and deploying production-grade AI systems powered by Large Language Models (LLMs). Specialized in Retrieval-Augmented Generation (RAG), AI agents, and scalable backend architectures using Python, FastAPI, Node.js, and .NET. Proven track record of designing end-to-end AI solutions, from data pipelines and embeddings to model integration, evaluation, and deployment on AWS. Experienced in developing high-performance AI microservices, semantic search systems, and intelligent automation workflows that drive measurable business impact. Strong focus on clean architecture, scalability, and LLMOps best practices to deliver reliable, production-ready AI applications.

Current Focus

  • Designing and deploying LLM-powered systems using RAG, embeddings, and vector databases for scalable knowledge retrieval
  • Building AI agents and multi-agent workflows using tool/function calling for autonomous task execution
  • Developing high-performance AI microservices with Python (FastAPI), Node.js, and .NET in distributed architectures
  • Implementing LLMOps practices including evaluation, monitoring, and optimization for production AI systems
  • Optimizing AI system performance through caching, batching, and efficient inference strategies
  • Deploying cloud-native AI solutions on AWS using Docker and CI/CD with focus on scalability and reliability

Achievements

  • Delivered 10+ production-grade AI applications integrating LLMs, RAG pipelines, and semantic search into real-world systems
  • Reduced manual workflows by up to 40% through AI-driven automation using NLP pipelines and intelligent agents
  • Improved system performance and scalability by up to 60% via optimized backend architectures and vector search integration
  • Led end-to-end development of AI platforms including conversational AI, knowledge retrieval systems, and automation tools
  • Deployed scalable AI infrastructure on AWS with high availability, observability, and cost-efficient architecture

Tech Stack

Technologies and tools I use to build exceptional digital experiences.

AI Engineering

LLMGenerative AIRAGPrompt EngineeringAI System DesignLangChainLlamaIndexEmbeddingsVector SearchSemantic SearchAI AgentsTool CallingFine-TuningLLMOpsOpenAI

Backend

Node.jsExpress.jsNestJSPythonDjangoFastAPI.NET / ASP.NET CoreREST APIsGraphQLMicroservices ArchitectureOAuth / SSO

Database

MongoDBPostgreSQLEntity Framework CoreADO.NETRedisPrismaTypeORMSequelizeFirebase

Frontend

JavaScriptTypeScriptReactNext.jsVue.jsReduxAngularBlazorHTML5CSS3Tailwind CSS

DevOps & Tools

GitGitHubPostmanJiraClickUpAWSDockerVercelHerokuCI/CDSDLCGoogle Analytics (GA)

APIs & Services

Google Maps APIStripePayPalPayment GatewaysGTM (Google Tag Manager)Meta PixelSSOSwaggerFirebase

6+

Years Experience

20+

Technologies Mastered

10+

Projects Completed

Professional Experience

A journey of growth, innovation, and delivering exceptional results

Senior AI Engineer

Turing

San Francisco, California
12/2024 - Present
Current
Python
FastAPI
LLM
RAG
LangChain
LangGraph
LlamaIndex
Prompt Engineering
Embeddings
Vector Databases (Pinecone, ChromaDB)
Semantic Search
AI Agents
Multi-Agent Systems
Tool Calling
Function Calling
Fine-Tuning
RLHF
MLflow
OpenAI
Hugging Face
Transformers
AWS
Docker
Kubernetes
Kafka
CI/CD
Microservices
  • •Architected and deployed production-grade LLM-powered applications using RAG pipelines, improving response accuracy and contextual relevance across enterprise workflows.
  • •Built scalable AI microservices using Python and FastAPI to support real-time inference, high-throughput processing, and low-latency AI APIs.
  • •Developed advanced multi-agent AI systems using LangGraph and tool/function calling for autonomous workflow execution and decision-making.
  • •Implemented vector search systems using Pinecone and ChromaDB, enabling semantic search and knowledge retrieval across large-scale datasets.
  • •Fine-tuned transformer models and applied RLHF techniques to improve model performance, alignment, and domain-specific accuracy.
  • •Designed end-to-end ML pipelines with MLflow for experiment tracking, evaluation, and continuous model improvement (LLMOps).
  • •Integrated OpenAI, Hugging Face, and open-source LLMs into enterprise platforms for conversational AI, automation, and intelligent assistants.
  • •Optimized AI system performance, reducing inference latency and improving throughput through model optimization and caching strategies.
  • •Led cross-functional AI initiatives, mentoring engineers and driving adoption of AI-first architecture across products.

AI Engineer

Devbridge

Chicago, Illinois
06/2021 - 11/2024
Python
FastAPI
Node.js
LLM
RAG
LangChain
Prompt Engineering
Embeddings
Semantic Search
Vector Databases
OpenAI
Hugging Face
Transformers
Recommendation Systems
NLP
React
GraphQL
MongoDB
PostgreSQL
AWS
Docker
CI/CD
Microservices
  • •Developed AI-powered full-stack applications integrating LLM-based features such as intelligent search, conversational assistants, and recommendation systems.
  • •Designed and implemented RAG pipelines connecting LLMs with structured and unstructured enterprise data sources.
  • •Built backend AI services using Python (FastAPI) and Node.js within scalable microservices architectures.
  • •Applied NLP techniques and transformer-based models for text processing, classification, and semantic understanding.
  • •Implemented embedding-based retrieval systems to enhance search relevance and user experience.
  • •Integrated OpenAI and Hugging Face models for content generation, summarization, and workflow automation.
  • •Improved user engagement and system efficiency by ~30% through AI-driven personalization and recommendations.
  • •Collaborated across teams to transition traditional systems into AI-enabled platforms.

Full Stack Developer

Onfleet

San Francisco, California
03/2020 - 05/2021
Python
FastAPI
Node.js
C#
.NET
ASP.NET Core
Distributed Systems
Event-Driven Architecture
Kafka
PostgreSQL
MongoDB
AWS
Docker
CI/CD
Data Pipelines
Scalable Systems Design
  • •Built scalable backend systems and REST APIs using Python (FastAPI), Node.js, and ASP.NET Core for high-performance applications.
  • •Developed and maintained backend services using C# and .NET, following clean architecture and modular design principles.
  • •Designed distributed, event-driven architectures using Kafka to support real-time data processing pipelines.
  • •Developed data-intensive systems that laid the foundation for AI/ML integration and intelligent workflows.
  • •Optimized database performance (PostgreSQL, MongoDB), reducing query latency and improving throughput.
  • •Implemented scalable cloud infrastructure on AWS ensuring reliability, fault tolerance, and performance.
  • •Contributed to early-stage AI readiness by structuring data pipelines and backend systems for future ML adoption.
  • •Collaborated on system design decisions focusing on scalability, maintainability, and data-driven architecture.

Projects

Amelia

Amelia

Enterprise Conversational AI Platform

An enterprise-grade AI platform leveraging LLMs, RAG pipelines, and multi-agent systems to automate complex workflows and deliver context-aware conversational experiences.

◎ Key Achievements

  • Designed RAG-based architecture using embeddings and vector databases
  • Built multi-agent workflows using LangGraph for complex reasoning tasks
  • Implemented LLM evaluation and prompt optimization strategies
  • Developed FastAPI-based microservices for real-time AI interactions
  • Enabled semantic search across enterprise datasets using vector retrieval
  • Deployed scalable AI systems on AWS ensuring high availability

Technologies

PythonFastAPILLMRAGLangGraphVector DatabasesSemantic SearchPrompt EngineeringAWSAI Agents
Sabermine

Sabermine

AI Document Processing System

An AI-powered document processing platform leveraging OCR and NLP to automate extraction, classification, and validation of structured and unstructured data.

◎ Key Achievements

  • Built OCR and NLP pipelines for extracting structured data from complex documents
  • Developed FastAPI microservices for scalable document processing workflows
  • Implemented entity recognition and classification using NLP techniques
  • Automated document validation workflows, reducing manual effort significantly
  • Designed multi-format processing pipelines for PDFs and images
  • Deployed scalable AI infrastructure on AWS for high-throughput processing

Technologies

PythonFastAPINLPOCRDocument AIAWSMicroservicesData ExtractionAutomation
SeekSocial

SeekSocial

Influencer discovery and engagement platform

A scalable platform enabling intelligent influencer discovery using search optimization, ranking systems, and high-performance backend services.

◎ Key Achievements

  • Developed advanced search and filtering features for influencer discovery
  • Implemented recommendation and ranking logic to improve user engagement
  • Integrated data-driven scoring mechanisms for better content relevance
  • Optimized backend performance using Node.js and MongoDB
  • Implemented RabbitMQ queues for faster data processing and requests
  • Reduced search latency through optimized indexing and query performance

Technologies

ReactNode.jsExpress.jsMongoDBRabbitMQAWSRecommendation SystemsSearch Optimization
Popless

Popless

Next-gen learning and teaching management platform

A scalable learning management platform enabling users to manage classes, payments, and educational workflows with efficient backend systems.

◎ Key Achievements

  • Developed backend services using ASP.NET Core and Nest.js for scalable system architecture
  • Designed clean architecture-based APIs ensuring maintainability and modularity
  • Optimized PostgreSQL database performance for secure and efficient data handling
  • Integrated Stripe for global payment processing and subscription management
  • Implemented GraphQL APIs to improve data fetching efficiency
  • Enhanced system scalability and performance through backend optimizations

Technologies

ASP.NET CoreC#.NETNestJSTypeScriptPostgreSQLGraphQLAWSDockerCI/CD
Glamezy

Glamezy

Beauty service booking platform

A scalable booking platform enabling users to discover, schedule, and manage beauty services with optimized workflows and intelligent user experience features.

◎ Key Achievements

  • Developed booking and scheduling features improving user experience and engagement
  • Integrated Stripe for secure and seamless payment processing
  • Implemented location-based services using Google Maps API for nearby discovery
  • Built responsive UI components using React and TypeScript
  • Optimized backend workflows, reducing booking confirmation time by 18%
  • Enhanced system reliability with improved API handling and error management

Technologies

NestJSReactTypeScriptPostgreSQLAWS S3StripeDockerGoogle Maps APIREST APIs
Designs.ai

Designs.ai

AI-powered design automation platform

An AI-driven creative platform enabling automated generation of marketing content using LLMs and multimodal generative AI workflows for text, images, and videos.

◎ Key Achievements

  • Developed LLM-powered content generation workflows for automated design and branding outputs
  • Integrated generative AI APIs for multimodal content creation including text, images, and video
  • Built scalable backend pipelines using Node.js and RabbitMQ for asynchronous AI processing
  • Optimized AI inference pipelines, reducing generation latency by 20%
  • Deployed AI workloads on AWS with high availability and scalable infrastructure
  • Implemented secure access controls for managing AI-generated assets and workflows

Technologies

React.jsNode.jsExpress.jsPostgreSQLLLMGenerative AIMultimodal AIAWSRabbitMQAI APIs
Oval

Oval

NFC-powered digital business card and networking platform

A cloud-based digital identity platform enabling seamless profile sharing through NFC and QR technologies, with scalable APIs and intelligent analytics for lead generation.

◎ Key Achievements

  • Developed NFC and QR-based sharing workflows, increasing lead generation efficiency by 30%
  • Built scalable backend systems using Nest.js and ASP.NET Core for enterprise-grade APIs
  • Integrated Stripe for secure payments and subscription workflows across distributed services
  • Implemented CI/CD pipelines and Docker deployments, reducing deployment time by 40%
  • Optimized MongoDB and SQL queries, improving API response performance by 25%
  • Introduced analytics and data tracking features to support intelligent business insights

Technologies

NestJSASP.NET CoreC#TypeScriptMongoDBAWSDockerStripeCI/CDData Analytics
LassWho

LassWho

Live video chat platform connecting fans with global icons

A real-time video communication platform enabling fans to interact with global personalities through secure, low-latency video calls, enhanced with intelligent personalization and scalable backend systems.

◎ Key Achievements

  • Developed WebRTC-based real-time video communication system, increasing user engagement by 30%
  • Built scalable backend services using ASP.NET Core and Node.js for secure session and API management
  • Implemented recommendation logic to personalize user sessions and improve discovery experience
  • Explored AI-based moderation techniques for real-time content filtering and user safety
  • Optimized PostgreSQL queries and backend workflows, improving data retrieval performance by 20%
  • Improved call reliability and system stability, achieving 98% uptime across devices

Technologies

Next.jsTypeScriptASP.NET CoreC#Node.jsPostgreSQLWebRTCAWSAI-based ModerationRecommendation Systems

Education

Bachelor OF Computer Science

San Francisco State University

2016 – 2020
  • ↗Gained a strong foundation in computer science principles, including algorithms, data structures, and software engineering.
  • ↗Completed projects on web development, database management, and mobile app development.
  • ↗Participated in tech seminars and coding competitions, improving problem-solving and teamwork skills.

Key Achievements

Notable accomplishments that demonstrate impact and innovation.

Professional Certifications

Recognized credentials demonstrating expertise in cloud technologies, DevOps practices, AI tooling, and modern development workflows.

  • AWS Certified Developer – Associate
  • LLM Applications Development with LangChain and OpenAI
  • ChatGPT Prompt Engineering for Developers
  • C# Design Patterns Certificate

Project Management Excellence

Successfully led multiple projects improving team efficiency and ensuring on-time deliveries.

  • Improved cross-team collaboration
  • 100% on-time delivery
  • 20% team efficiency boost
  • 3 concurrent projects

Performance Optimization

Delivered significant performance improvements across multiple systems and products.

  • 50% performance increase
  • 40% API response improvement
  • 30% UI optimization

Team Leadership

Led engineering teams and mentored junior developers while managing client expectations.

  • 6-person team leadership
  • Junior mentoring
  • Client project management
Contact Me

Get in Touch

I am always interested in discussing opportunities, projects, and ideas to create exceptional digital experiences.

Location

California, United States

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