job description
Join TTEC as an Agentic AI Engineer specializing in Googleās Agent Development Kit (ADK) and lead the future of autonomous AI systems in the heart of Bali. In this cutting-edge role, youāll design, develop, and deploy production-grade Multi-Agent Systems that redefine intelligent automation, leveraging Googleās latest AI frameworks to solve complex, real-world challenges.
As part of our dynamic team, youāll collaborate with cross-functional experts to architect scalable, self-orchestrating AI agents capable of reasoning, planning, and executing tasks with minimal human intervention. Your work will drive innovation in customer experience, operational efficiency, and decision-makingāall while enjoying Baliās vibrant tech ecosystem and work-life balance.
This is a unique opportunity to shape the next generation of AI at a global leader in digital transformation, with the flexibility of working from Baliās most sought-after locations.
Responsibility
- Design and implement Multi-Agent Systems using Google ADK, ensuring scalability, reliability, and real-time performance.
- Develop autonomous AI agents with advanced reasoning, tool-use, and collaborative capabilities.
- Optimize agent workflows for efficiency, cost, and latency in production environments.
- Integrate AI systems with enterprise APIs, databases, and third-party services.
- Conduct rigorous testing, validation, and debugging of agent behaviors and edge cases.
- Collaborate with data scientists and engineers to refine models, prompts, and evaluation metrics.
- Document architectures, best practices, and deployment pipelines for team adoption.
- Stay ahead of emerging trends in Agentic AI, LLM orchestration, and Google Cloud AI tools.
Qualifications
- Bachelorās or Masterās degree in Computer Science, AI, or a related field.
- 3+ years of experience in software engineering, AI/ML, or automation systems.
- Hands-on experience with Google ADK, Vertex AI, or similar agent frameworks (e.g., LangChain, CrewAI).
- Proficiency in Python, Java, or Go and modern cloud platforms (GCP preferred).
- Strong understanding of LLMs, prompt engineering, and RAG (Retrieval-Augmented Generation).
- Experience with distributed systems, microservices, or event-driven architectures.
- Familiarity with CI/CD pipelines, Docker, and Kubernetes for scalable deployments.
- Excellent problem-solving skills and a passion for building next-gen AI solutions.