JaCoCo Experts in Germany

IT consulting, analysis, architecture design, new and further development, code review, test automation, continuous integration, continuous delivery in backend and frontend areas for Automotive Project Instavalo.

Frontend:

• Implementation of UI components according to specifications, especially style guides and responsive design eith React and Typescript
• Component testing
• Code documentation
• CI/CD with Gitlab Pipeline

Backend / IoT:

• Analysis and architectural design with AWS Greengrass IoT on Edge Devices
• Setting up Microservices containers with Docker Compose on Edge device with AWS Greengrass and AWS IoT IAM, Token Exchange Service, Ansible
• CI/CD with Gitlab Pipeline, Terraform, AWS ECR
• Logging with Fluentbit Lua Language for AWS Cloudwatch
• Python Lambda for AWS Greengrass Recipe deployment on Edge Devices
• Implementation of test-driven development with JUnit, Mockito, and code Coverage
• Jacoco
• Definition of REST interfaces with OpenAPI / Swagger
• Development and enhancement of software based on Java Quarkus, Typescript NestJs NodeJs and Python
• Authentication and authorization in Aws IAM
• Development of REST and gRPC interfaces for the frontend and backend
• Implementation of Maven dependencies with DevSecOps OWASP
• Spring AI, Jetbrains AI Assistant, Junie, Github Copilot, Claude Code, Agents, Skills, Command, Hooks, Subagents

• Developed and deployed microservices in Kotlin and Spring Boot, integrated AWS Secrets Manager to secure credentials and decreased network calls using Spring cache.
• Refactored Kafka consumer using Spring Kafka with semaphore-based backpressure to cap records and keep heap memory stable under spikes; switched to batch upserts to cut down on database invocations; added Testcontainers integration tests for Kafka and database to pave the way for future changes.
• Automated the financial reconciliation workflow in Spring Boot (Kotlin) using Spring Scheduler, transactional boundaries, JPA/Hibernate on MySQL, and Flyway migrations, saving the accounts team 16+ hours per week.
• Designed and dockerized payments end-to-end test framework in Robot (Python) with reusable keyword libraries and profiles; integrated with GitLab CI (JaCoCo XML and HTML reports) to accelerate releases and lift code coverage to 80%.
• Implemented end-to-end observability on Datadog by instrumenting services with Datadog APM, correlating metrics and logs, provisioning dashboards, and creating monitors with burn-rate alerts and anomalies to harden reliability and give stakeholders clear visibility.

Leading the end-to-end development of Edge AI-powered smart glasses for visually impaired individuals, aligning product vision with user needs and managing a cross-functional team of data scientists, Android developers, AWS engineers, and hardware specialists.

• Defined product roadmap for Edge AI smart glasses and MVP features through user research, stakeholder interviews, and competitive analysis, ensuring accessibility and real-world usability.
• Developed and validated a PoC for AI-driven cancer cell identification in PET/CT scans, collaborating with medical experts to optimize diagnostic accuracy and clinical relevance.
• Built and scaled a multidisciplinary team of 75+ engineers, interns, and designers across Germany and India, driving cross-border collaboration and iterative prototyping.
• Established strategic partnerships with NGOs, healthcare providers, and advocacy groups to embed inclusivity and patient feedback into product design.
• Drove hands-on hardware-software integration using Raspberry Pi and Jetson Nano of AI models. Initiated and nurtured relationships with suppliers, manufacturers, and ecosystem players to build scalable go-to-market plans.
• Owned critical product decisions, from prototype development to funding strategy, applying a data-informed and impact-driven mindset.
• Fostered a learning-focused culture by facilitating brainstorming sessions and continuous feedback loops between engineering and product.

Achievements:

• Public speaker: Auto.Ai 2025 (Berlin), Wearable technologies 2025 (Munich and Bangalore), MEDICA 2024 (Dusseldorf)
• WMF, Bologna, Italy (June 2024): Only AI startup to be selected from Germany as EBV hero to represent sprhava on global platform
• Medica, Germany (2024): Delivered a speech on AI smart glasses in world's largest Healthcare event.
• Wearable Technologies, Bengaluru, India (Dec 2024): I was a speaker presenting sprhava and its product.
• Venturise Global Challenge (GIM 2025, Bengaluru Palace, Karnataka): sprhava was selected as one of the 16 top startups (ESDM) to present on this global platform
• Wearable Technologies Conference 2025 EUROPE, Munich, Germany (May 2025): Delivered a talk on Edge AI at the Europe's biggest wearable tech event.
• InsurNext Köln, Germany (2025): sprhava was honoured with a booth from Cologne administration.

• Development of microservices according to the TMF standard
• Adaptation of existing workflows to microservices (PNMGT, RADIUS, WBCI, ACS, VOIP, P2P)
• Migration of communication from RabbitMQ/REST to Kafka
• Development of Camunda processes for billing leased infrastructure
• Implementation of Kafka connectors for billing and inventory data systems
• Automation of the workflow for WBCI preliminary coordination
• Execution of unit and integration tests as well as acceptance tests with the business departments
• Setup of CI/CD pipelines
• Error analysis for support tickets
• Execution of larger refactorings of legacy code to adapt it to new microservices
• Participation in meetings to gather and clarify requirements
• Technologies: Kubernetes, AWS-DevOps, Apache Camel, Debezium, Python, TMF, Confluent, Kafka, OpenAPI, Java 21, Spring Boot, Docker, MapStruct, PostgreSQL, Maven, Camunda, Keycloak

• Product responsibility for the central platform "one" as a group-wide web-based customer portal
• Coordination of the connection of 20 group companies to the product platform
• Derivation and steering of a group-wide product strategy and roadmap aligned with company goals
• Prioritization and bundling of strategic requirements from the various group companies
• Harmonization of different interests and moderation of complex decision-making processes at management level
• Ensuring the technical and business integration of the product into existing system landscapes, business processes, and business models
• Building transparent governance and decision-making structures for group-wide product development
• Representation of the product towards internal and external stakeholders at leadership level

• Involved in the full development lifecycle, including design, coding, testing, and deployment of Java-based applications.
• Built and maintained high-performance RESTful APIs and microservices, ensuring scalability and reliable data exchange.
• Practiced code reviews, used version control systems (e.g., Git), and collaborated closely with cross-functional teams to deliver robust software solutions.
• Implemented, managed, and optimized complex business logic and decision-making processes using the Drools Rules Engine, leveraging DRL (Drools Rule Language) for dynamic configuration.
• Developed software solutions for a major service provider in the healthcare insurance sector, specifically focusing on claims processing and reconciliation logic to ensure cost-effective reimbursement for health funds.

Refactoring the CRM system of an IT service provider This includes a complete refactoring of the legacy application, in particular the migration from JDK 1.6 to JDK 25 and the replacement of self-developed infrastructure components, such as the Object-Relational Mapper (ORM) and the frontend template engine, with current standard components based on Spring Boot. At the same time, the previous close coupling between the back end and front end is being removed and the application is being migrated to a modern microservice architecture. The microservices are implemented as independent, reusable units and operated in autonomous Docker containers. The backend components are provided through REST APIs. As part of the project, CI/CD and deployment processes for the container-based microservice architecture were also established and automated using GitLab CI. At the same time, quality assurance is ensured through the implementation and automation of unit, integration and system tests. The work is supported by AI, particularly through the use of GitHub Copilot and LM Studio (gpt-oss) for code development and prompt engineering. Position: Software development, software quality assurance, tester, test automation engineer

Work performed:

• Analysis of the functional and technical use cases (workflows, involved processes/systems, communication paths, security requirements)
• Code refactoring (code cleanup, optimization)
• Dependency refactoring
• Refactoring of REST services (SpringBoot)
• Refactoring of the ORM layer
• Test execution / test automation (Serenity, Selenium, Playwright, JUnit)
• Establishment and automation of CI/CD pipelines for build, test and deployment steps in a Docker/microservice environment Team size: 2 people IT basis: Technologies: Java (JDK 25), Spring Boot, Hibernate, JPA, SQLServer, MariaDB, Docker, Yaml, Markdown, JSON, HTML/CSS, REST Tools: IntelliJ, DBeaver, Git/GitLab, GitHubCopilot (AI) Work management: Gitlab Tests: Serenity, Selenium, Playwright, JUnit Platform: Linux, Windows Version control: Gitlab Build management: Gitlab CI

• Taking over operational acceptance tests for internal and external applications in a preproduction environment
• End-to-end tests across multiple systems
• Planning and implementation of acceptances based on expected loads and service levels
• Creation of test plans and automated tests
• Monitoring of systems, log analysis and creation of test reports, monitoring charts and acceptance documentation
• Support during rollouts of security and OS patches in preproduction
• Load and performance tests as well as failover/rollback tests
• Testing SOAP/REST APIs with JMeter, Grafana and Kibana
• Batch tests with Bash and log analysis
• Load and performance tests of own applications
• Test automation with JMeter and PyTest
• Maintenance and creation of Bash scripting tests
• Manual system integration tests

• Support and further development of a framework for developing applications in a banking association: DynS/OSPE
• Migration of the framework to Java 11 and Java 17
• Java8, Java11 and Java17, Spring, Spring-Batch, Spring WebServices, Spring-Security, Spring-Data, JPA, Hibernate, OpenSource libraries etc.
• XML, JAXB, JSON, REST and SOAP services, DB2, Oracle, WebSphere or Liberty AS, FreeMaker, Junit, mock libraries, JaCoCo, Maven, IntelliJ, Eclipse, GitHub, SVN, Jira

• Data transformations
• IT company with more than 100 employees
• Software production
• Data augmentation and normalization, image transformation, format conversion, merging data from multiple sources
• Toolset: Java, Helm, Kubernetes, Kafka, OpenCV, IntelliJ IDEA, Gradle, Git, Docker, Containers, Scrum

• Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
• Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
• Responsible for webinar:
• IoT edge computing: architecture, components, resources, management
• IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
• IoT processes, connectivity, data transfer and deployment, security
• Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
• Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
• Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
• Analysis of large sensor data sets with Apache Spark, Kafka clusters
• Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
• Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
• Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))

• Developed backend systems for the DWS Investment App, a white-label investment solution (robo-advisor), and an investment solution for institutional clients.
• Java 8-17, Kotlin, Spring Boot, Spring MVC, OpenAPI 3.0, JPA, JDBI, Oracle, Hazelcast, JXLS, Apache POI, Apache PDFBox, Apache Kafka & Avro, Active MQ, Elasticsearch, React Native, Spock Test, IntelliJ IDEA, Kubernetes, Helm, Microservices/Netflix-Stack, TeamCity, Splunk.
• Kanban team, continuous integration.
• Migrated existing applications from Deutsche Bank's private cloud environment to Azure as part of a carve-out.