• Design, build, and deploy **production-grade GenAI solutions** (AI agents, copilots, RAG pipelines) with a focus on scalability, reliability, and performance • Own **end-to-end architecture** of AI systems on Azure, including integration with enterprise data platforms and backend services • Lead the development of **LLM-powered applications** using Azure-native services and modern orchestration frameworks • Implement **LLMOps practices**, including monitoring, logging, evaluation, prompt/version management, and cost optimization • Translate business requirements into **technical AI solutions** and define scalable implementation strategies • Ensure **security, governance, and compliance** across all AI solutions • Optimize AI systems for **latency, cost, and accuracy** in production environments • Provide **technical leadership**, mentor engineers, and drive best practices in system design and code quality

Role Description The Telesales Team is engaged in customer acquisition via phone sales. The team supports a number of call centers by providing a web-based working environment and telephony capabilities to hundreds of sales agents. Telesales is responsible for web tools for client acquisition, customer call strategies, agent performance evaluation, and more. As an AI Engineer in Telesales, you will primarily focus on developing LLM-based solutions for end-to-end sales automation and communication quality evaluation. - Develop our in-house AI sales bot solution for end-to-end sales automation. - Integrate with external vendors to evaluate and test third-party AI products and capabilities. - Build our in-house call analysis solution to identify critical agent mistakes and detect negative customer reactions. - Work closely with the team to launch robust AI solutions into production. - Take part in shaping new AI use cases in Telesales as the product evolves. Qualifications - Hands-on experience building LLM-based products or features for real business use cases. - Strong practical skills in prompt engineering, model integration, and designing reliable AI workflows. - Experience developing and launching AI solutions such as assistants, bots, or text analysis systems. - Good knowledge of Python and confidence working with modern AI tooling. - Strong engineering judgment and a pragmatic approach to solving product problems. - Ability to work independently and take ownership of AI solutions from idea to production. - Excellent communication skills and ability to collaborate with product and engineering teams. - B1 or higher English level for effective communication with an international team. Requirements - Previous experience delivering business-critical AI-powered applications. - Experience working on telesales, call center, or customer communication products. - Experience evaluating third-party AI solutions and comparing them against in-house approaches. - Experience with voice AI, speech analytics, or call quality evaluation solutions. Benefits - Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family. - Flexible work from one of our offices or remotely within time zones from GMT-2 to GMT+5. - Healthcare coverage. - Education Budget: Language lessons, professional training and certifications. - Wellness Budget: Mental health and fitness activity reimbursements. - Vacation policy: 20 days of annual leave and paid sick leave.

(English below) À propos de Waveshaper AI Waveshaper AI révolutionne le traitement audio grâce à une intelligence artificielle prête pour l’edge computing, apportant un son de qualité studio à tout appareil. Notre technologie brevetée d’apprentissage audio-à-audio alimente des modèles neuronaux ultra-légers pour un traitement audio en temps réel. À propos du poste Nous recherchons un(e) Ingénieur(e) Senior en IA Audio ayant un esprit entrepreneurial pour développer des modèles neuronaux audio destinés au déploiement sur des appareils edge. Vous stimulerez l’innovation en apprentissage machine tout en évoluant rapidement dans un environnement startup. Responsabilités principales : 1. Développement ML Audio - Concevoir et entraîner des modèles neuronaux pour le traitement audio (réduction de bruit, amélioration de la parole, amélioration de la qualité) - Évaluer la qualité audio via des écoutes subjectives et des métriques objectives - Construire des pipelines ML évolutifs et des stratégies de données audio - Développer des architectures de modèles optimisées pour des applications audio en temps réel 2. Optimisation et Déploiement de Modèles - Mettre en œuvre des techniques de compression, quantification et élagage de modèles - Optimiser les modèles ML pour les appareils edge avec des contraintes mémoire et de latence - Déployer les modèles sur diverses plateformes et configurations matérielles - Construire des pipelines MLOps pour l’entraînement, la gestion des versions et le déploiement automatisé 3. Innovation en Startup - Prendre des décisions techniques malgré des informations incomplètes et itérer rapidement - Travailler directement avec les clients pour valider les solutions et recueillir des retours - Trouver l’équilibre entre excellence technique et délais de livraison produit - Transformer des avancées en IA audio en fonctionnalités prêtes pour le marché Qualifications recherchées : Expertise Audio & ML - 5+ ans d’expérience en traitement du signal audio et développement de modèles ML - Excellente compréhension des métriques de qualité audio et du traitement perceptif - Expérience des architectures de réseaux neuronaux pour applications audio - Maîtrise de TensorFlow, PyTorch et frameworks ML audio Optimisation des Modèles - 3+ ans d’expérience en compression de modèles et déploiement edge - Connaissance des techniques de quantification, élagage et distillation - Compréhension de l’optimisation sous contraintes de ressources - Expérience en MLOps et systèmes ML en production Esprit Startup - Motivation entrepreneuriale, capacité à évoluer rapidement et à s’adapter - Expérience avec les plateformes cloud (GCP/AWS) et l’infrastructure ML - Solides compétences en programmation Python et ingénierie des données - Capacité à travailler dans des environnements dynamiques et en évolution rapide Qualifications souhaitées : - Diplôme en informatique, ingénierie ou domaine connexe - Expérience dans l’industrie audio ou les systèmes audio en temps réel - Expérience avec des frameworks ML edge (TensorFlow Lite, ONNX) - Expérience en environnement startup Ce que nous offrons : - Responsabilités techniques sur une technologie IA audio de pointe. - Autonomie technique et impact direct sur le produit - Rémunération compétitive à Montréal (options de télétravail disponibles) Prêt(e) à révolutionner l’IA audio ? Rejoignez-nous pour construire un traitement audio intelligent pour les appareils edge. _____________ About Waveshaper AI Waveshaper AI revolutionizes audio processing with edge-ready AI that brings studio-quality sound to any device. Our patented audio-to-audio learning technology powers ultra-lightweight neural models for real-time audio processing. About the Role We're seeking a Senior Audio AI Engineer with an entrepreneurial mindset to develop neural audio models for edge deployment. Drive breakthrough ML innovations while moving fast in a startup environment. Key Responsibilities : 1. Audio ML Development - Design and train neural audio processing models for noise reduction, speech enhancement, and quality improvement - Evaluate audio quality using both subjective listening and objective metrics - Build scalable ML pipelines and audio data strategies - Develop model architectures optimized for real-time audio applications 2. Model Optimization & Deployment - Implement model compression, quantization, and pruning techniques - Optimize ML models for edge devices with memory and latency constraints - Deploy models across diverse platforms and hardware configurations - Build MLOps pipelines for training, versioning, and automated deployment 3. Startup Innovation - Make technical decisions with incomplete information and iterate rapidly - Work directly with customers to validate solutions and gather feedback - Balance technical excellence with product delivery timelines - Translate audio AI breakthroughs into market-ready features Qualifications : Audio & ML Expertise - 5+ years audio signal processing and ML model development - Deep understanding of audio quality metrics and perceptual audio processing - Experience with neural network architectures for audio applications - Proficiency with TensorFlow, PyTorch, and audio ML frameworks Model Optimization - 3+ years experience with model compression and edge deployment - Knowledge of quantization, pruning, and distillation techniques - Understanding of resource-constrained optimization - Experience with MLOps and production ML systems Startup Mindset - Entrepreneurial drive to move fast and adapt quickly - Experience with cloud platforms (GCP/AWS) and ML infrastructure - Strong Python programming and data engineering skills - Ability to work in fast-paced, evolving environments Preferred Qualifications : - Degree in Computer Science, Engineering, or related field - Audio industry or real-time audio systems experience - Experience with edge ML frameworks (TensorFlow Lite, ONNX) - Startup environment experience What We Offer : - Technical ownership of cutting-edge audio AI technology - Technical autonomy and direct product impact - Competitive package in Montreal (remote options available) Ready to revolutionize audio AI? Join us in building intelligent audio processing for edge devices

Important Information Location: BrazilJob Mode: Full-time Work Mode: Work from home Job Summary As a Fullstack AI Engineer, you will play a key role in the full development lifecycle of a high-impact Generative AI MVP, translating complex architectural requirements into technical solutions. You will be responsible for building the bridge between Azure AI Foundry agents and the end-user, developing robust APIs, integrating RAG (Retrieval-Augmented Generation) pipelines, and implementing a simplified frontend. Beyond technical execution, you will collaborate closely with an AI Specialist and stakeholders to ensure the delivery of an explainable and compliant solution within an Agile framework. Responsibilities and Duties - Digest requirements from the architecture and product team to specify the implementation of new features from a fullstack and AI-integration perspective; - Implement the designed solution from coding to testing, focusing on Azure Functions, API development, and agentic workflows; - Follow Agile processes and participate actively in all development phases to ensure a functional MVP within 3 months; - Development of new features, including data connectors for Excel/Word and tool orchestration for LLM agents; - Design and maintain the application's frontend to provide a seamless interface for "Well Engineers"; - Participate in the complete cycle of development from requirements gathering, RAG data ingestion, to final deployment; - Participate in technical discussions, demonstrations, and reviews with customers (Halliburton/Petrobras context). Essential Skills - Solid Experience with Python (preferred) or Node.js; - Frameworks: ReactJS for frontend development; - AI Integration: Experience with LangChain, Semantic Kernel, or similar LLM orchestration frameworks; - Cloud Knowledge: Solid experience with Azure (Functions, App Service, and Blob Storage); - API Development: Experience with REST APIs and integrating third-party AI services; - Data Handling: Experience processing structured and unstructured data (Excel/Word) for AI consumption; - Solid experience with Git. Highly Desirable Skills - Experience with Azure AI Foundry and Azure AI Search; - Knowledge of Vector Databases and RAG architectures; - Experience with automated testing (Unit, Integration) for AI-driven applications; - Familiarity with AI Observability tools (Tracing, Prompt Logging); - Experience with Tailwind CSS or fast prototyping UI libraries; - Knowledge of Docker and CI/CD pipelines within Azure DevOps. About EncoraEncora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.