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Senior Software Engineer with 8 years of experience delivering AI/ML platforms across cloud environments, with hands-on experience running training and inference workloads on Google Cloud alongside AWS. Skilled in architecting distributed serving infrastructure, streaming data pipelines, and MLOps automation to shorten release cycles. Leads cross-functional engineering teams while staying close to platform and model code. Comfortable working across multi-cloud ML environments and building production-ready LLM/RAG applications with observability and security guardrails.…Senior Software Engineer with 8 years of experience delivering AI/ML platforms across cloud environments, with hands-on experience running training and inference workloads on Google Cloud alongside AWS. Skilled in architecting distributed serving infrastructure, streaming data pipelines, and MLOps automation to shorten release cycles. Leads cross-functional engineering teams while staying close to platform and model code. Comfortable working across multi-cloud ML environments and building production-ready LLM/RAG applications with observability and security guardrails.

Sam Sharif

Software Engineer, AI Engineer, Data Engineer, +2

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Senior Software Engineer with 8 years of experience delivering AI/ML platforms across cloud environments, with hands-on experience running training and inference workloads on Google Cloud alongside AWS. Skilled in architecting distributed serving infrastructure, streaming data pipelines, and MLOps automation to shorten release cycles. Leads cross-functional engineering teams while staying close to platform and model code. Comfortable working across multi-cloud ML environments and building production-ready LLM/RAG applications with observability and security guardrails.…Senior Software Engineer with 8 years of experience delivering AI/ML platforms across cloud environments, with hands-on experience running training and inference workloads on Google Cloud alongside AWS. Skilled in architecting distributed serving infrastructure, streaming data pipelines, and MLOps automation to shorten release cycles. Leads cross-functional engineering teams while staying close to platform and model code. Comfortable working across multi-cloud ML environments and building production-ready LLM/RAG applications with observability and security guardrails.

Available to hire

Senior Software Engineer with 8 years of experience delivering AI/ML platforms across cloud environments, with hands-on experience running training and inference workloads on Google Cloud alongside AWS. Skilled in architecting distributed serving infrastructure, streaming data pipelines, and MLOps automation to shorten release cycles.

Leads cross-functional engineering teams while staying close to platform and model code. Comfortable working across multi-cloud ML environments and building production-ready LLM/RAG applications with observability and security guardrails.

Skills

Experience Level

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Intermediate

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Beginner

Work Experience

Senior Software Engineer at Futran Solutions

February 1, 2022 - Present

Deployed cloud-native AI pipelines on GCP AI Platform (Vertex AI) and AWS, integrating models into GraphQL/REST APIs with automated retraining. Architected and led enterprise AI/ML platforms across ingestion, training, and inference, directing cross-functional engineering teams while maintaining alignment with underlying platform and model code. Scaled distributed model serving infrastructure on Kubernetes (KServe, Triton, EKS/Kubeflow), reducing p99 latency by 25–35% and lowering GPU costs. Migrated batch ML pipelines to streaming architecture (Kafka, Flink), reducing data freshness lag from hours to minutes. Built production LLM/RAG applications using LangChain, LangGraph, Pinecone, Weaviate, and FAISS, cutting research/lookup time by 30–40%, and adding observability and security guardrails (Prometheus, Grafana, LangSmith, prompt-injection mitigation). Led 8–10 engineers and automated code review workflows (Cloud Code, Copilot), reducing PR review time by ~20%, and built real-t

Software Engineer at DMI

August 1, 2019 - January 31, 2022

Built ETL/ELT pipelines (Airflow, Spark, Dask, Pandas) to prepare and validate training datasets at scale, improving reliability. Designed Kafka-based event-driven architectures for real-time data streaming and ML preprocessing. Developed and productionized ML models (TensorFlow, PyTorch, XGBoost) for classification, forecasting, and recommendations, improving accuracy up to 28%. Built recommendation systems and fraud/anomaly-detection models, improving forecast accuracy by ~18%. Deployed containerized services (Docker, Kubernetes) to AWS via Terraform, reducing deployment downtime by ~35%, and designed backend APIs (FastAPI, Flask, Node.js) for model predictions. Optimized database queries (PostgreSQL, MySQL) by ~30% and introduced automated testing/data validation (Pytest, Jest, Great Expectations) across pipelines and features.

Full Stack Engineer at Remote Reps

May 1, 2017 - July 31, 2019

Built ETL/ELT pipelines (Airflow, Spark, Dask, Pandas) for large-scale training dataset preparation and validation. Designed Kafka-based event-driven architectures for real-time data streaming and preprocessing. Developed ML models (TensorFlow, PyTorch, XGBoost) for classification, forecasting, and recommendations, improving accuracy up to 28%. Built recommendation and anomaly-detection systems for financial/fraud use cases, improving accuracy by ~18%. Deployed containerized services to AWS (EC2, ECS, SageMaker) via Terraform, reducing downtime by ~35%, and built backend APIs (FastAPI, Flask, Node.js) for model serving. Optimized database performance (~30% faster) and introduced automated testing/data-validation practices to reduce post-release issues.