Unifonic

• Setting up and enhancing CI (Continuous Integration) and CD (Continuous Deployment). • Configuring the company's products to meet the functional requirements, including the configuration of functional areas and technical areas. • Troubleshooting and remediating issues impacting the integration and operations of the infrastructure and systems. • Ensuring high availability of the company’s products and platforms [24x7x365]. • Writing and deploying scripts in different environments to automate day-to-day operations. • Maintaining servers’ configuration, monitoring jobs, and infrastructure documentation across the cloud environment.

• Owning the reliability, uptime, and scalability of critical production services 24/7. • Participating in the on-call rotation to respond to incidents, troubleshoot live production issues, and lead post-incident analysis. • Building robust operational playbooks, escalation paths, and improve Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR). • Ensuring operational excellence by proactively detecting and addressing reliability risks through SLO monitoring, chaos testing, and capacity planning. • Automating operational tasks to minimize human intervention. • Architecting, implementing, and managing infrastructure across AWS, Oracle Cloud Infrastructure (OCI), and OpenStack environments. • Optimizing cloud resources to balance performance, security, and cost-efficiency. • Managing Kubernetes clusters (EKS, OKE, Rancher RKE2) for scalability, availability, and performance. • Managing and optimizing high-performance messaging and caching systems including Kafka, RabbitMQ, and Redis. • Managing and optimizing production-grade MySQL and PostgreSQL databases. • Leading the planning and execution of comprehensive disaster recovery strategies. • Implementing advanced observability solutions (Prometheus, Grafana, CloudWatch). • Driving automation initiatives using Terraform, Helm, Jenkins, Tekton or GitLab CI/CD. • Integrating security best practices into infrastructure and applications. • Collaborating with cross-functional teams to foster SRE culture and mentoring junior engineers.

• Improve product ceremonies, planning processes, and operational frameworks continuously that support product teams. • Help structure and prepare inputs for product planning sessions and roadmap reviews. • Identify operational gaps and propose improvements to strengthen product team focus and effectiveness. • Standardize product reporting, metrics, and operational insights to support decision-making. • Promote adoption of AI tools and automation to improve product operations workflows, reporting, and knowledge sharing. • Design and lead Product Enablement programs for internal teams (Sales, Customer Success, Customer Support, Presales). • Support product launches, demos, and rollouts, ensuring internal stakeholders understand product capabilities and value. • Translate complex product capabilities into clear messaging, demos, and use cases. • Help drive product awareness and adoption across the organization. • Work closely with Product, Design, Engineering, Commercial, and Marketing teams to understand customer needs and market trends. • Identify customer use cases and solution patterns that can inform product evolution and commercial opportunities. • Synthesize data from various sources (customer feedback, analytics, sales insights, market research) into actionable recommendations. • Support Product leaders in communicating product strategy and impact through clear insights and communication. • Help identify new product growth opportunities and remove operational or adoption barriers. • Collaborate with Marketing and Commercial teams to highlight product success stories and drive product awareness. • Act as a go-to person for product knowledge and market insights within the organization.

• Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures. • Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content. • Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction. • Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search). • Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches. • Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products. • Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks. • Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI). • Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode. • Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations. • Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA. • Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture. • Assisting in the project documentation and demos.

• Leading a team that designs and delivers a drag-and-drop workflow builder powered by Camunda • Building and maintaining integration connectors with various platforms • Ensuring the reliability and scalability of communication solutions • Supporting recruitment, hiring, and onboarding of engineering talent • Driving architecture decisions for scalable and maintainable systems • Communicating status, risks, and requirements clearly across stakeholders • Facilitating continuous learning and improvement for the team

• Design and implement test strategies, automation frameworks, and CI/CD integrations that ensure our systems meet the highest standards of quality and performance. • Collaborate closely with developers, product owners, and DevOps engineers to build robust automation pipelines for UI, API, and backend testing. • Contribute to load and performance testing initiatives. • Designing, building, and maintaining automated test frameworks for UI, API, and backend testing using Playwright, Cypress, or Selenium. • Developing and executing integration and end-to-end test suites to ensure high-quality releases. • Implementing performance and load testing using k6 or similar tools. • Integrating automated testing into CI/CD pipelines (Git, Drone CI, Argo CD, Kubernetes). • Driving test coverage, defect reporting, and quality metrics across multiple delivery teams. • Collaborating with engineers to embed testing early in the SDLC and ensure reliable, scalable automation. • Advocating for QA best practices, code quality, and automation-first principles. • Leading continuous improvement initiatives evaluating new tools, frameworks, and techniques to enhance efficiency and maintainability.