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I am Muhammad Shoaib, a Senior AI Engineer and LLM Architect focused on building cloud-native AI platforms. I design and deploy real-time inference, low-latency LLM serving, and AI-first APIs using Python, FastAPI, and distributed microservices. My work spans ML, deep learning, and Generative AI, including LLMs, Transformers, RAG, embeddings, prompt engineering, and agent-based workflows. With 10+ years in backend, ML, and MLOps/LLMOps, I architect scalable AI infrastructure across AWS, GCP, and Azure, leaning on Kubernetes, Docker, Terraform, and observability tooling. I specialize in end-to-end AI platforms, from data ingestion to model governance, safe rollbacks, and regulated deployments, delivering high-throughput, observable systems and actionable insights to enterprise teams.…I am Muhammad Shoaib, a Senior AI Engineer and LLM Architect focused on building cloud-native AI platforms. I design and deploy real-time inference, low-latency LLM serving, and AI-first APIs using Python, FastAPI, and distributed microservices. My work spans ML, deep learning, and Generative AI, including LLMs, Transformers, RAG, embeddings, prompt engineering, and agent-based workflows. With 10+ years in backend, ML, and MLOps/LLMOps, I architect scalable AI infrastructure across AWS, GCP, and Azure, leaning on Kubernetes, Docker, Terraform, and observability tooling. I specialize in end-to-end AI platforms, from data ingestion to model governance, safe rollbacks, and regulated deployments, delivering high-throughput, observable systems and actionable insights to enterprise teams.

Muhammad Shoaib

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am Muhammad Shoaib, a Senior AI Engineer and LLM Architect focused on building cloud-native AI platforms. I design and deploy real-time inference, low-latency LLM serving, and AI-first APIs using Python, FastAPI, and distributed microservices. My work spans ML, deep learning, and Generative AI, including LLMs, Transformers, RAG, embeddings, prompt engineering, and agent-based workflows. With 10+ years in backend, ML, and MLOps/LLMOps, I architect scalable AI infrastructure across AWS, GCP, and Azure, leaning on Kubernetes, Docker, Terraform, and observability tooling. I specialize in end-to-end AI platforms, from data ingestion to model governance, safe rollbacks, and regulated deployments, delivering high-throughput, observable systems and actionable insights to enterprise teams.…I am Muhammad Shoaib, a Senior AI Engineer and LLM Architect focused on building cloud-native AI platforms. I design and deploy real-time inference, low-latency LLM serving, and AI-first APIs using Python, FastAPI, and distributed microservices. My work spans ML, deep learning, and Generative AI, including LLMs, Transformers, RAG, embeddings, prompt engineering, and agent-based workflows. With 10+ years in backend, ML, and MLOps/LLMOps, I architect scalable AI infrastructure across AWS, GCP, and Azure, leaning on Kubernetes, Docker, Terraform, and observability tooling. I specialize in end-to-end AI platforms, from data ingestion to model governance, safe rollbacks, and regulated deployments, delivering high-throughput, observable systems and actionable insights to enterprise teams.

Available to hire

I am Muhammad Shoaib, a Senior AI Engineer and LLM Architect focused on building cloud-native AI platforms. I design and deploy real-time inference, low-latency LLM serving, and AI-first APIs using Python, FastAPI, and distributed microservices. My work spans ML, deep learning, and Generative AI, including LLMs, Transformers, RAG, embeddings, prompt engineering, and agent-based workflows.

With 10+ years in backend, ML, and MLOps/LLMOps, I architect scalable AI infrastructure across AWS, GCP, and Azure, leaning on Kubernetes, Docker, Terraform, and observability tooling. I specialize in end-to-end AI platforms, from data ingestion to model governance, safe rollbacks, and regulated deployments, delivering high-throughput, observable systems and actionable insights to enterprise teams.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Senior AI / Backend Engineer at MILLER ELECTRIC COMPANY

January 1, 2022 - Present

Architected and delivered a real-time, AI-driven building intelligence platform using Python, FastAPI, and cloud-native microservices to monitor and control HVAC, energy, fire alarm, and security systems across large commercial environments. Productionized ML and GenAI pipelines for anomaly detection, predictive maintenance, and operational intelligence, combining classical ML with LLM-assisted reasoning to contextualize alerts and surface actionable insights from high-frequency IoT telemetry. Led Retrieval-Augmented Generation (RAG) workflows powering an LLM-based field engineer assistant, incorporating embedding pipelines, chunking strategies, vector search (FAISS, Pinecone), and LangChain-based retrieval and reasoning. Implemented agent-style reasoning with LangGraph to model multi-step diagnostic flows while maintaining deterministic execution and observability. Integrated structured domain knowledge for building systems and equipment hierarchies to ground LLM responses and reduce

Software Engineer – Network & Data Backend Services at T-MOBILE

March 1, 2019 - January 1, 2022

Designed and developed high-throughput backend microservices in Java and Python supporting customer applications, service activation, device lifecycle, and network integrations, leveraging REST APIs, Kafka, PostgreSQL, and Redis for real-time operations. Built scalable backend systems for 5G network service provisioning, orchestration, and monitoring, using stateless microservices, gRPC, Kubernetes, and CI/CD pipelines to ensure low-latency, high-availability services across millions of subscribers. Developed secure enterprise and partner-facing API platforms with Spring Cloud, OAuth2, and AWS, exposing connectivity, device management, and usage analytics services while ensuring scalability, fault tolerance, and monitoring. Engineered data ingestion, processing, and analytics backend pipelines using Python, Spark, Kafka, SQL, and Airflow, providing internal dashboards and operational insights for network performance and customer metrics. Integrated ML/AI-powered automation features int

Senior Software Engineer at MYMATRIX

August 1, 2016 - March 1, 2019

Lead architecture and development of Python-based microservices supporting real-time claims adjudication, eligibility checks, and utilization management, integrating REST APIs, PostgreSQL, Redis, and message queues for high-throughput and fault-tolerant backend systems. Designed and implemented Python backend APIs powering the myPassport portal and enterprise integrations, handling full lifecycle claims, authorizations, billing, and reporting, with secure OAuth2-based authentication, transactional integrity, and scalable architecture. Engineered Python backend pipelines for processing large-scale pharmacy and clinical datasets, enabling data-driven insights, analytics dashboards, and ML-ready data preparation for intelligent clinical decision support. Developed backend automation engines and rule-based workflows for proactive alerts and drug utilization reviews, integrating event-driven architecture and scalable Python services to reduce inappropriate medication use. Built RESTful APIs

Software Engineer at ASSISTRX

February 1, 2014 - August 1, 2016

Lead design and development of Python backend microservices powering real-time benefit verification and eligibility services, integrating direct connections with payers, PBMs, and specialty pharmacy systems to accelerate access to therapy and optimize request turnaround times. Architected and implemented backend systems for ePrior Authorization (ePA) workflows within the iAssist platform, using Python, REST APIs, and async processing to automate prior authorization submissions and return payer decisions in near real-time, dramatically reducing manual overhead. Built robust Python APIs to enable secure data exchange between provider portals, EHR systems, and specialty pharmacy networks, including support for electronic prescribing, eConsent, and enrollment services with compliance and audit logging. Engineered backend data pipelines to ingest, validate, and process large volumes of pharmacy and patient access data, utilizing Python ETL workflows, SQL databases, caching (Redis), and mess