# Mohith D > Software Engineer | 5+ Years Experience | Backend • Distributed Systems • High-Scale Systems | Kafka • Kubernetes • AWS Location: South San Francisco, California, United States Profile: https://flows.cv/mohithd Software Engineer with 5+ years of experience in building scalable backend and distributed systems. Experienced in designing high-throughput, low-latency services using Python, Kafka, Kubernetes, and AWS. Passionate about system design, performance optimization, and building reliable, production-grade infrastructure at scale. ## Work Experience ### Software Engineer @ Meta Jan 2024 – Present • Built a scalable recommendation backend using Python, FastAPI, and Django, serving 2M+ users with <200ms p95 latency at 10k+ RPS. • Deployed services on Kubernetes-based distributed infrastructure, enabling auto-scaling, high availability, and fault tolerance. • Developed hybrid recommendation systems (collaborative + content-based) with LLM embeddings and vector search (FAISS, Pinecone), improving cold-start accuracy by 35% • Designed and delivered RESTful APIs and async GraphQL services with 99.99% uptime under high traffic • Optimized PostgreSQL with sharding, indexing, and Redis caching to handle 5M+ daily events efficiently • Built CI/CD pipelines (GitHub Actions, Jenkins) for automated testing, containerization, and Kubernetes deployments • Created ETL pipelines using PySpark and SQL to process large-scale user interaction data • Implemented real-time streaming with Kafka and Spark Streaming for instant recommendation updates • Developed async systems with Celery, RabbitMQ, and Kafka for background processing and model retraining • Used MLflow for A/B testing and model tracking, improving CTR, retention, and engagement • Achieved 95%+ test coverage using PyTest for reliable deployments • Designed highly scalable systems with rate limiting, retries, circuit breakers, handling up to 50k RPS • Set up monitoring and observability (Prometheus, Grafana, ELK) and built dashboards using React & TypeScript • Ensured secure and compliant systems with OAuth2, JWT, GDPR, and SOC2 standards ### Software Engineer @ Goldman Sachs Jan 2020 – Jan 2023 • Engineered and scaled internal AI developer tools using Python, streamlining model development, testing, and deployment workflows, improving developer productivity by 35%. • Built and productionized RESTful APIs and GraphQL services using FastAPI and Flask, enabling flexible, real-time AI/ML inference and seamless integration across internal financial platforms. • Architected high-performance async and distributed systems using FastAPI, Celery, and RabbitMQ, supporting low-latencyinference and scalable background processing for compute-intensive workloads. • Designed scalable microservices architecture and leveraged Flask for rapid prototyping, accelerating feature development cycles and system modularity. • Developed end-to-end ML pipelines and reusable SDKs covering data preprocessing, feature engineering, model training, evaluation, benchmarking, and experiment tracking (MLflow), improving reproducibility and experimentation speed. • Implemented LLM-powered features (prompt engineering, embeddings, semantic search) and built RAG pipelines, enabling context-aware, intelligent responses over large-scale document corpora. • Deployed scalable AI/ML systems on AWS (S3, EC2, Lambda, API Gateway), optimizing for cost, performance, and highavailability in cloud-native environments. • Designed and implemented secure, scalable backend architectures with OAuth2/JWT authentication, rate limiting, caching, and horizontal scaling to support high-throughput financial systems. • Containerized applications using Docker and orchestrated deployments with Kubernetes, enabling auto-scaling, fault tolerance, and high availability. • Built and optimized data storage and caching layers using PostgreSQL, MongoDB, and Redis, ensuring low-latency access and high-throughput data processing. • Processed large-scale financial datasets using Apache Spark and PySpark and integrated real-time streaming with Kafka, enabling continuous ingestion and near real-time analytics. ## Education ### Master's degree in Computer Science Saint Louis University ## Contact & Social - LinkedIn: https://linkedin.com/in/shiv9876 --- Source: https://flows.cv/mohithd JSON Resume: https://flows.cv/mohithd/resume.json Last updated: 2026-04-16