AI Engineer: LLM Applications & Cloud-Native Systems

IAN FARAI MADHARA

AI ENGINEER LLM APPLICATIONS AI PLATFORMS CLOUD-NATIVE SYSTEMS

Queens, NY (Open to Relocate) 201-***-**** *************@*****.*** LinkedIn PROFESSIONAL SUMMARY

AI Engineer and software engineer with experience building production AI applications, LLM-powered workflows, model evaluation systems, inference services, and cloud-native backend platforms. Experienced integrating OpenAI and Anthropic Claude APIs, evaluating open-weight language models, developing Python services with Django and FastAPI, and deploying containerized workloads on Kubernetes and Azure Kubernetes Service. Combines applied AI experience with a strong foundation in distributed systems, microservices, Java, Spring Boot, AWS, Azure, CI/CD, observability, and production reliability. CORE TECHNICAL SKILLS

LLM & Generative AI: OpenAI APIs · Anthropic Claude · LLM Application Development · Open-Weight Language Models · Prompt Engineering · AI Agents · Agentic Workflows · Model Orchestration · LLM Evaluation · Model Benchmarking · Inference Optimization

AI & Machine Learning: TensorFlow · Model Inference · Model Evaluation · Predictive Modeling · Feature Engineering · Neural Networks · ML Pipelines · AI Experimentation

Programming & Application Engineering: Python · Java · JavaScript · React · Django · FastAPI · Spring Boot · REST APIs · Microservices · Backend Architecture · Distributed Systems · Asynchronous Services Cloud & Infrastructure: AWS · Microsoft Azure · Azure Kubernetes Service · Kubernetes · Docker · Helm · Linux · Cloud-Native Architecture · Containerized AI Services · Production Deployments MLOps & Reliability: CI/CD · Jenkins · AI/ML Deployment · Inference Services · Production Monitoring · Observability · Performance Optimization · Reliability Engineering · Prometheus · Grafana · Splunk · AppDynamics Data & Integration: SQL · PostgreSQL · ETL Pipelines · Data Processing · Data Transformation · Data Validation · API Integration · Algorithm Development

PROFESSIONAL EXPERIENCE

APTEAN — Remote May 2026 – Present

AI Engineer

• Engineer production AI applications integrating OpenAI and Anthropic Claude APIs with custom TensorFlow components to support agent-based workflows and enterprise automation use cases.

• Build Python-based AI services using Django, FastAPI, and REST APIs, connecting model inference, application logic, backend services, and business workflows.

• Design multi-provider model integration services that support multiple foundation-model APIs, model configurations, and workload requirements.

• Evaluate model behavior across response quality, latency, reliability, and workload fit to inform model-selection and AI application architecture decisions.

• Deploy containerized AI workloads using Docker, Kubernetes, and Helm on Azure Kubernetes Service, supporting scalable and maintainable production services.

• Integrate AI capabilities into React-based user experiences and Python backend services, connecting the LLM, application, and infrastructure layers.

ALPHIENT AI — London, England, UK Remote Jan 2026 – May 2026 AI Research & Engineering Intern

• Engineered LLM-powered automation workflows integrated with backend applications, contributing to an approximately 30% improvement in workflow efficiency.

• Evaluated self-hosted open-weight language models as alternatives to proprietary inference APIs, reducing targeted inference costs by approximately 60–80%.

• Benchmarked 10+ language models across response quality, latency, inference cost, throughput, deployment complexity, and operational fit.

• Built comparative evaluation workflows to assess model quality, performance, cost, and deployment trade-offs across proprietary and open-weight models.

• Optimized model-selection and inference approaches, contributing to an approximately 40% latency improvement across targeted AI workflows.

ENTELECT — Johannesburg, South Africa Sep 2022 – Jul 2024 Intermediate Software Engineer

• Designed and developed Java Spring Boot microservices supporting a large-scale banking platform serving more than 10 million users and approximately 50,000 requests per second.

• Built cloud-native backend services using AWS, Docker, Kubernetes, and Jenkins CI/CD to support automated build, testing, deployment, and production operations.

• Diagnosed and resolved memory leaks across logging and security components, contributing to an approximately 25% reduction in production outages.

• Implemented production observability using Prometheus, Grafana, and Kubernetes monitoring, contributing to approximately 99.9% service availability.

• Developed AWS migration tooling and infrastructure improvements that reduced targeted cloud costs by approximately 10% while improving application scalability.

ECOCASH HOLDING — Harare, Zimbabwe Oct 2020 – Sep 2022 Software Engineer

• Developed Java and React capabilities for the Maisha health-information platform, supporting billing, account management, and customer-facing workflows.

• Designed and implemented backend billing and client-management functionality across Java services and React-based application interfaces.

• Developed ETL pipelines and data-processing algorithms to identify duplicate and anomalous billing patterns across customer accounts.

• Implemented application monitoring using Splunk and AppDynamics, contributing to an approximately 10% improvement in system availability.

EDUCATION

• Master of Science in Artificial Intelligence May 2026 GPA: 3.8/4.0

— YESHIVA UNIVERSITY — Katz School of Science and Health

• Bachelor of Science Honours in Business Studies & Computing Science Dec 2020 GPA: 4.0/4.0

— UNIVERSITY OF ZIMBABWE

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