Veeranjaneyulu Batthula
AI/ML Automation Engineer
Professional Summary
Software Development Engineer Intern candidate with strong foundations in data structures, algorithms, and object-oriented design. Hands-on experience designing and building scalable, cloud-native services, ML-backed applications, and distributed systems using Python, Java, and AWS/Azure. Proven ability to take end-to-end ownership of solutions, from design and development to deployment, monitoring, and documentation, in agile, fast-paced environments.
Professional Experience
AI/ML Automation Engineer
Bank of America, UK
September 2023 – Present
- Proposed data processing pipelines using Python and SQL for enterprise-scale data analytics
- Created predictive services integrated into business workflows, improving operational efficiency
- Built end-to-end AI automation workflows integrating Azure DevOps, internal APIs, Logic Apps, and Power Automate to standardize project telemetry and reduce manual operations
- Developed and deployed LLM-powered services (Azure OpenAI, RAG, vector search) for automated summaries, onboarding guidance, and decision support, optimizing cost per token and throughput
- Owned observability for AI and platform workloads using Grafana, Prometheus, Thanos, ELK, and Splunk to track latency, GPU utilization, and LLM performance
- Managed and optimized large-scale Kubernetes environments with autoscaling and GPU resource optimization for AI/ML workloads
- Delivered executive-level insights via Power BI dashboards and ensured production reliability through end-to-end QA, validation, and post-deployment tuning
Awards & Recognition
- Employee of the Month
- Best Performer Award
Research Assistant
University of East London, England
October 2024 – May 2025
- Planned and adopted algorithms for data processing and model evaluation in academic research projects
- Wrote clean, well-documented code and comprehensive technical documentation
- Addressed large datasets and optimized performance of data pipelines for research applications
- Collaborated with academic and industry stakeholders to deliver reliable software solutions
AI Engineer
V2 Software Solutions
January 2020 – August 2023
- Designed and deployed LLM-powered systems automating internal workflows and customer support, reducing manual effort and improving response accuracy
- Collaborated with software engineering, product and business teams to define architecture, shape technical requirements and guide feature integration
- Built scalable backend services and APIs in Python to handle high-volume traffic while ensuring performance and reliability
- Architected distributed training and inference pipelines using Kubernetes, carefully managing GPU/CPU resources, autoscaling, and secure access controls
- Defined and implemented MLOps practices: model versioning, continuous integration/deployment, automated testing, monitoring, and lifecycle management
- Applied modular monolith and SOA design patterns to support long-term maintainability and allow incremental AI feature adoption across the platform
- Integrated security best practices and responsible AI standards, including static code analysis, access control and ML-specific risk mitigation
- Provided technical leadership, conducted design reviews, mentored engineers and acted as trusted advisors for AI strategy across teams
Technical Skills
Programming Languages
Python, PyTorch, TensorFlow, Hugging Face, Java, PowerShell, JavaScript
Software Development
RESTful APIs, Microservices Architecture, CI/CD Pipelines, Version Control (Git), Code Reviews, Agile/Scrum, Debugging, Troubleshooting, Logging, Monitoring
Cloud & Distributed Systems
AWS (EC2, S3, Lambda, IAM), Azure Cloud, Scalable & Fault-Tolerant Systems, SQL & NoSQL Databases
AI & Machine Learning
Machine Learning fundamentals, LLM-based applications, GenAI tools, Model deployment, Inference pipelines, RAG, Vector Search
AI Automation Stack
Power Automate, Power BI, Copilot Studio, Copilot Agent, Semantic Kernel
MLOps Tools
MLflow, Docker, Kubernetes, GPU utilization optimization, AI workload optimization
Observability Tools
Grafana, Prometheus, Thanos, Elasticsearch, Kibana, Splunk
Platforms & Databases
Visual Studio, Azure DevOps, SQL Server, Azure Data Lake, Power Platform, Excel-based data sources
Projects
Scalable AI-Powered Web Service
- Architected a microservice-based backend using Python and REST APIs
- Deployed on AWS with CI/CD pipelines and basic monitoring
- Implemented scalable architecture to handle high-volume traffic efficiently
Automated Accessibility Analysis System
- Established an AI-driven system to analyse website accessibility using WCAG guidelines
- Delivered a production-ready solution with clear technical documentation
- Automated compliance checking and reporting for accessibility standards
Certifications & Awards
Education
Master of Science in Computer Science
University of East London, England
2024
Bachelor of Science in Computer Science
Jawaharlal Nehru Technological University (JNTU)
2019
