Role Description This role focuses on building and maintaining scalable, secure backend systems using Python and cloud technologies. The candidate will design RESTful APIs and microservices, integrate third-party solutions like Pindrop, and develop high-performance applications on AWS. The role involves working extensively with cloud services (Lambda, S3, DynamoDB), implementing CI/CD pipelines, ensuring system observability, and contributing to infrastructure automation. Additionally, the candidate will support contact center transformation initiatives, including integrations with Amazon Connect, while collaborating across teams to deliver reliable and efficient solutions. Responsibilities - Design, develop, and maintain RESTful APIs and microservices using Python. - Integrate and support Pindrop solutions including authentication, fraud detection workflows, and SDK/API usage. - Architect secure, scalable, and high-performance backend applications. - Integrate backend services with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, and DynamoDB. - Write clean, efficient, testable code following best practices for performance, maintainability, and security. - Design and deploy cloud-native applications using AWS services including EC2, Lambda, S3, RDS, DynamoDB, API Gateway, and IAM. - Implement and maintain CI/CD pipelines using GitHub Actions or GitLab CI. - Set up monitoring, logging, and observability using CloudWatch, CloudTrail, and Splunk logging. - Collaborate on infrastructure automation using CloudFormation and Terraform. - Integrate solutions with AWS services like Lambda. - Use of AI-assisted coding in development workflows. - Assist in migration projects from legacy contact center platforms to Amazon Connect. - Contribute to frontend work (React/Angular/Vue) when needed and ensure smooth integration with backend APIs. Qualifications - 5-7 years of experience in backend development. - 5+ years of experience in cloud-based application engineering. - 5+ years of experience with Python, Node.js, C#, or Java (Python required). - Hands-on experience with Pindrop integrations including risk scoring, authentication workflows, and troubleshooting. - Knowledge of telephony concepts and SIP trunking. - Experience with AWS SDKs, reporting, analytics, and troubleshooting. - Deep experience designing and implementing RESTful APIs and microservices. - Hands-on experience with SQL and NoSQL databases. - Strong understanding of authentication, authorization, and security best practices. - Extensive experience with AWS services including EC2, Lambda, S3, IAM, RDS, DynamoDB, and VPC. - Proficiency in CI/CD pipeline setup and maintenance. - Experience with CloudFormation and Terraform for infrastructure as code. - Understanding of networking and cloud security best practices. Nice to Have - Experience with Amazon Connect integrations, including API usage, contact flow design, routing, queues, and call-flow troubleshooting. - Experience or knowledge of using AI and LLM models. - Basic proficiency in frontend development (JavaScript, HTML5, CSS3). - Familiarity with React, Angular, or Vue.js frameworks. - Understanding of responsive UI/UX design principles. - AWS Certifications (Cloud Practitioner, Developer Associate, Solutions Architect Associate). - Experience with event-driven architectures (SNS, SQS, EventBridge). Benefits - Culture of Relentless Performance: join an unstoppable technology development team with a 99% project success rate and more than 30% year-over-year revenue growth. - Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, language courses, and a relocation program. - Work From Anywhere Culture: make the most of the flexibility that comes with remote work. - Growth Mindset: reap the benefits of a range of professional development opportunities, including certification programs, mentorship and talent investment programs, internal mobility and internship opportunities. - Global Impact: collaborate on impactful projects for top global clients and shape the future of industries. - Welcoming Multicultural Environment: be a part of a dynamic, global team and thrive in an inclusive and supportive work environment with open communication and regular team-building company social events. - Social Sustainability Values: join our sustainable business practices focused on five pillars, including IT education, community empowerment, fair operating practices, environmental sustainability, and gender equality.

Role Description V4C.ai is seeking a highly experienced Senior .NET Microservices Developer to join our dynamic development team. In this role, you will design, develop, and maintain scalable microservices-based applications, primarily using .NET technologies. Your expertise will help enhance the robustness and performance of our distributed systems while collaborating closely with cross-functional teams to deliver high-quality solutions. Qualifications - Extensive experience (8+ years) in developing microservices-based applications using .NET Core and C#. - Strong knowledge of RESTful API design, development, and integration. - Experience with containerization technologies such as Docker and orchestration tools like Kubernetes. - Proficient in working with messaging systems such as RabbitMQ, Kafka, or Azure Service Bus. - Solid understanding of cloud platforms (Azure, AWS, or GCP) and deploying microservices in these environments. - Experience with CI/CD pipelines and automated testing frameworks. - Familiarity with database technologies including SQL Server, NoSQL databases, and ORM tools like Entity Framework. - Ability to design systems with high availability, scalability, and security in mind. - Strong troubleshooting and debugging skills. - Excellent communication skills and the ability to work effectively in a collaborative team environment. Requirements - Experience with event-driven architecture and CQRS patterns. - Familiarity with API gateways and service meshes (such as Istio or Linkerd). - Knowledge of monitoring and logging tools like Prometheus, Grafana, or ELK stack. - Experience mentoring junior developers and leading technical discussions.

• API Development: Design, build, and maintain RESTful APIs using .NET C#, focusing on performance, reliability, and security. • Entity Framework & SQL: Develop efficient data models using Entity Framework Core, and write optimized SQL queries for relational databases like SQL Server. • Cloud Transition Support: Contribute to new development efforts that utilize Azure services (e.g., Azure Functions, App Services, Azure SQL) as we begin migrating from on-prem infrastructure. • Machine Learning Integration: Collaborate with stakeholders to integrate machine learning models via RESTful APIs or Azure ML services. • Clean, Maintainable Code: Follow best practices to write testable, maintainable, and well-documented code. • Cross-Team Collaboration: Work closely with fellow developers and business partners to deliver secure, scalable solutions. • CI/CD Practices: Support continuous integration and delivery efforts using tools like GitHub Actions. • Problem Solving: Investigate and resolve performance issues, bugs, and bottlenecks in existing systems.

• The work involves designing and implementing AI solutions aligned with business needs and technological standards. • It includes applying techniques like Retrieval-Augmented Generation (RAG) to improve the precision and relevance of AI interactions. • Developing Agentic RAGs, which incorporate autonomous agents to refine data retrieval and content generation. • Developing AI agents and agent networks, capable of solving complex problems and interacting with each other. • Using tools such as LangChain to create modular architectures for agents. • Designing and managing data ingestion pipelines, implementing serverless architectures and Pub/Sub models to scale data intake. • Using DevOps and MLOps practices for automating the deployment and management of AI models. • Integrating APIs to connect AI models with external systems and to register events and metadata. • Performance optimization includes analyzing system performance, detecting bottlenecks, and implementing caching strategies to improve response times. • Emphasizing collaboration with designers and product teams to ensure AI solutions meet real business and user needs, while maintaining innovation through continuous research and experimentation with new AI technologies.