• Design and implement real-time voice agents using ASR, TTS, and LLM-based reasoning. • Evaluate Voice Agent providers, focussing on reliability and stress testing • Build multi-turn, stateful voice conversations with interruption handling (barge-in), retries, tool-use and fallbacks. • Build evaluation for AI Agent performance, ensuring that AI Agents are working as expected • Finetune and adapt STT (Speech to Text), TTS (Text to speech) and LLMs for different dialects • Contribute to the development of the Lucidya AI Agent platform, ensuring that Voice capability is embedded in the platform • Deploy AI models into production environments with a focus on scalability, performance, and reliability. • Collaborate on MLOps practices to support continuous integration, monitoring, and improvement. • Work with streaming architectures (WebSockets, gRPC, SIP/WebRTC). • Analyse call logs and transcripts to continuously improve performance. • Work closely with software engineers, product managers, and domain experts • Translate business problems into effective AI solutions with measurable outcomes. • Ensure AI solutions comply with ethical standards, data privacy requirements, and legal regulations. • Document models, algorithms, workflows, and decisions clearly for internal and external stakeholders. • Stay up to date with the latest AI research, tools, and best practices; and apply them where valuable.

• As an AI Engineer, you will be the bridge between "what’s next" and "what works." • Lead technical execution in cloud-native environments (GCP/AWS) and build prototypes that solve real-world problems. • Own the technical delivery of innovation-focused initiatives from concept to implementation. • Collaborate with cross-functional teams to identify opportunities and shape solutions. • Rapidly prototype and iterate on new applications or internal tools to validate ideas. • Design, build, and deploy AI-enabled solutions using services like Vertex AI, LangChain, and LLM APIs. • Integrate machine learning models into internal tools, workflows, and user-facing products. • Develop prompt engineering workflows, orchestration patterns, and scalable AI solutions. • Architect cloud-native solutions in GCP and AWS, using best practices in scalability, security, and automation. • Implement infrastructure as code using tools such as Terraform or CloudFormation. • Support automation, API integration, and serverless deployments across multiple environments. • Contribute across a wide range of engineering activities, including scripting, automation, cloud setup, and backend development. • Solve ambiguous or undefined technical problems with practical and creative solutions. • Provide support for troubleshooting, debugging, and optimizing solutions post-deployment. • Evaluate emerging technologies and frameworks and recommend potential applications to support internal and external initiatives. • Document and share findings with internal teams to drive knowledge sharing and reusability.

• Projektowanie i budowa systemów Agent AI jako część skomplikowanych, produkcyjnych platform • Współpraca z zespołami międzyfunkcyjnymi w celu zdefiniowania architektury i kierunku technicznego w całym cyklu życia, od wczesnej eksploracji do produkcji • Kierowanie i wpływanie na dyskusje dotyczące systemów i architektury, zapewniając, że rozwiązania AI są skalowalne, niezawodne, wydajne i łatwe w utrzymaniu w dłuższej perspektywie • Działanie jako zaufany doradca techniczny, kwestionując założenia, jasno formułując problemy i proponując dobrze uzasadnione rozwiązania inżynieryjne zamiast po prostu wykonywać zadania • Praca rąk na obu backendach i frontendach, z głównym zarządzaniem systemami backendowymi • Pewna współpraca w środowisku z klientem i wielu dostawcami oraz wzmacnianie naszego eksperckiego stanowiska poprzez silną wiarygodność techniczną i jasną komunikację

• Collaborate closely with Agentic AI Scientists and product teams to design, build, and deploy agentic AI systems that automate and optimize labor-intensive workflows while enabling the human workforce with new, AI-powered capabilities. • Develop and maintain full-stack software that supports agentic AI workflows. • Build user-facing interfaces and tools, implementing backend services and APIs, and writing application logic that enables agent communication, orchestration, and tool use. • Integrate AI models and agents with external systems and services via APIs, supporting testing and debugging, deploying solutions into target environments, configuring monitoring and logging, and ensuring reliable, secure execution of agentic AI systems in production. • Work with a mix of open-source models, agentic frameworks, and proprietary commercial AI services. • Contribute to the development of approaches for securing agentic workflows and for evaluating system behavior with respect to accuracy, performance, reliability, and mission impact. • Help ensure that AI systems adhere to ethical guidelines and principles of transparency, accountability, and fairness. • Conduct applied research, develop prototypes, and evaluate and document results, including contributing to technical reports, publications, or conference presentations.