About the company:
Avenue Code is the leading software consultancy focused on delivering end-to-end development solutions for digital transformation across every vertical. We’re privately held, profitable, and have been on a solid growth trajectory since day one. We care deeply about our clients, our partners, and our people. We prefer the word ‘partner’ over ‘vendor’, and our investment in professional relationships is a reflection of that philosophy. We pride ourselves on our technical acumen, our collaborative problem-solving ability, and the warm professionalism of our teams.
Avenue Code has been believing in and promoting plurality actions for over 10 years, understanding that recognizing differences and fostering a safe environment, employment opportunities, representation, and support are the best ways to promote an increasingly equitable culture.
About the opportunity:
The Conversational lA Infrastructure Engineer is a critical role focused on bridging the gap between lA-driven conversational solutions and the underlying communications infrastructure. This role involves designing, developing, and deploying systems that integrate advanced AI technologies, such as natural language processing (NLP), speech recognition, and large language models (LLMs), with infrastructure components such as IVR/URA, VolP, and networking systems.
The ideal candidate will have a solid background in AI applications and practical experience with contact center technologies, ensuring seamless and innovative communication solutions powered by AI.
Responsibilities:
- Design, develop and implement lA-driven conversational systems that integrate with IVR/URA, VolP and network infrastructures.
- Collaborate with cross-functional teams to align LA solutions with existing communications systems, ensuring robust and scalable deployments.
- Develop and optimize speech recognition, text-to-speech (TTS) and PLN/NLP for use in conversational lA applications.
- Work with Python and deep learning frameworks (e.g. PyTorch, TensorFlow) to build and deploy conversational LA models.
- Integrate chatbots, voice assistants, and other conversational AI technologies into contact center platforms.
- Troubleshoot and optimize lA systems to ensure high performance and reliability in communications infrastructure.
- Stay up to date with advances in LA technologies and infrastructure, applying best practices to improve system performance and user experience.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Applied Mathematics or related field.
- Proven experience or training in Computer Science, Technology, Mathematics or related areas.
- Hands-on experience developing and deploying conversational AI applications, including chatbots, voice assistants, or similar technologies.
- Experience in speech recognition, PLN/NLP, TTS and related algorithms.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Hands-on experience with contact center technologies and platforms, including systems.
Nice to Have:
- Knowledge of cloud platforms, with a preference for Google Cloud.
- Experience with cloud-based ML platforms (e.g. Google Cloud Vertex Al, Dialogflow, CCAIP).
- Experience in building and deploying commercial and open-source speech recognition systems.
- Understanding of large language models (LLMS), including their architecture, training methodologies, and fine-tuning techniques.
- Familiarity with speech processing tools and frameworks
Avenue Code reinforces its commitment to privacy and to all the principles guaranteed by the most accurate global data protection laws, such as GDPR, LGPD, CCPA and CPRA. The Candidate data shared with Avenue Code will be kept confidential and will not be transmitted to disinterested third parties, nor will it be used for purposes other than the application for open positions. As a Consultancy company, Avenue Code may share your information with its clients and other Companies from the CompassUol Group to which Avenue Code’s consultants are allocated to perform its services.
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