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Senior AI/ML and Full Stack Engineer with 7+ years building production-grade backend systems and 4+ years deep expertise in GenAI, RAG architectures, and agentic multi-agent systems. Proven track record designing and deploying GraphRAG pipelines and LLM-powered applications with a strong focus on accuracy, scalability, and real-world reliability. Experienced across the full AI lifecycle—from ML model development and ETL for unstructured data to RAG evaluation using frameworks like Ragas and TruLens. Builds robust APIs and services using Python, Django, Flask/FastAPI with testing, CI/CD, and performance optimization for low-latency, high-throughput applications.…Senior AI/ML and Full Stack Engineer with 7+ years building production-grade backend systems and 4+ years deep expertise in GenAI, RAG architectures, and agentic multi-agent systems. Proven track record designing and deploying GraphRAG pipelines and LLM-powered applications with a strong focus on accuracy, scalability, and real-world reliability. Experienced across the full AI lifecycle—from ML model development and ETL for unstructured data to RAG evaluation using frameworks like Ragas and TruLens. Builds robust APIs and services using Python, Django, Flask/FastAPI with testing, CI/CD, and performance optimization for low-latency, high-throughput applications.

Talha Asif

AI Engineer, Full Stack Developer, Back-End Developer, +1

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Senior AI/ML and Full Stack Engineer with 7+ years building production-grade backend systems and 4+ years deep expertise in GenAI, RAG architectures, and agentic multi-agent systems. Proven track record designing and deploying GraphRAG pipelines and LLM-powered applications with a strong focus on accuracy, scalability, and real-world reliability. Experienced across the full AI lifecycle—from ML model development and ETL for unstructured data to RAG evaluation using frameworks like Ragas and TruLens. Builds robust APIs and services using Python, Django, Flask/FastAPI with testing, CI/CD, and performance optimization for low-latency, high-throughput applications.…Senior AI/ML and Full Stack Engineer with 7+ years building production-grade backend systems and 4+ years deep expertise in GenAI, RAG architectures, and agentic multi-agent systems. Proven track record designing and deploying GraphRAG pipelines and LLM-powered applications with a strong focus on accuracy, scalability, and real-world reliability. Experienced across the full AI lifecycle—from ML model development and ETL for unstructured data to RAG evaluation using frameworks like Ragas and TruLens. Builds robust APIs and services using Python, Django, Flask/FastAPI with testing, CI/CD, and performance optimization for low-latency, high-throughput applications.

Available to hire

Senior AI/ML and Full Stack Engineer with 7+ years building production-grade backend systems and 4+ years deep expertise in GenAI, RAG architectures, and agentic multi-agent systems. Proven track record designing and deploying GraphRAG pipelines and LLM-powered applications with a strong focus on accuracy, scalability, and real-world reliability.

Experienced across the full AI lifecycle—from ML model development and ETL for unstructured data to RAG evaluation using frameworks like Ragas and TruLens. Builds robust APIs and services using Python, Django, Flask/FastAPI with testing, CI/CD, and performance optimization for low-latency, high-throughput applications.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Beginner

Beginner

Beginner

Language

English

Advanced

Urdu

Advanced

Work Experience

AI & ML Engineer (Senior) / Full Stack Developer (AI/ML) at Verdant Soft

May 1, 2024 - Present

Engineered rigorous TDD coverage across Django REST APIs and the end-to-end RAG pipeline from preprocessing and retrieval to agentic AI generation. Developed and evaluated end-to-end RAG systems exposed via Django/FastAPI endpoints, improving output quality through embedding optimization, reranking, and hallucination mitigation. Designed Django-integrated ETL pipelines for telecom banking clients transforming unstructured data (PDFs, SQL, web) into high-quality inputs for ML and agentic AI systems. Built low-latency Django backends using Redis, GPT caching, and batch processing workflows for scalable high-throughput AI/ML applications. Integrated Google Gemini and Azure OpenAI APIs within Django-based backends to support autonomous agentic decision-making in healthcare and telecom environments.

AI Engineer (Advanced AI Systems) / Back-End Engineer at AI Systems (FastAPI services; Crypto/trading environment)

April 1, 2022 - April 1, 2024

Architected production-grade FastAPI microservices for real-time cryptocurrency aggregation, handling high-concurrency requests from 20+ global exchanges simultaneously. Engineered multi-layer Redis caching and optimized connection pooling to achieve sub-millisecond data retrieval for high-frequency trading and real-time trend analysis. Built fault-tolerant ETL pipelines processing millions of daily market signals with strict data validation schemas, maintaining 99.9% data accuracy across unstructured sources. Leveraged async Python (asyncio) and Celery task queues for horizontal scaling and background processing, reducing server-side response times by 45%. Established TDD practices using PyTest with automated CI/CD pipelines to ensure high test coverage across mission-critical financial data flows.

AI Python Developer at Tech Bridge Consultancy

March 1, 2020 - May 1, 2022

Architected and deployed scalable FastAPI and Django backends as serving layers for AI/ML models, enabling secure, high-performance model inference endpoints containerized via Docker on AWS. Built an IoT-integrated data pipeline using ZK Tecodevices and Raspberry Pi for real-time edge data collection and automated preprocessing feeding downstream ML model training workflows. Optimized PostgreSQL schemas and query performance to support low-latency retrieval of large structured datasets, accelerating ML training cycles and reducing data bottlenecks in AI inference pipelines. Designed Celery task queues with Redis for scalable AI job scheduling and orchestration handling asynchronous model inference requests, background data ingestion, and automated ML pipeline execution at scale.

Back-End Developer (Python) at Ibrahim Developers

March 1, 2019 - February 1, 2020

Architected and deployed scalable production-grade REST APIs using Django and FastAPI with secure API integration, containerized deployments via Docker, and AWS cloud infrastructure management. Engineered an IoT-powered attendance management system integrating ZK biometric devices and Raspberry Pi, improving operational efficiency by 40% through real-time hardware-software synchronization. Optimized PostgreSQL schemas, indexing strategies, and query performance—reducing data retrieval times by 35% and improving application responsiveness under load. Designed and maintained Celery task queues with Redis as a message broker enabling reliable background job scheduling and asynchronous processing for high-demand workflows.