Avaya is seeking a Lead AI Application Engineer to design, develop, and deploy advanced Generative AI and Agentic AI applications to solve complex problems and drive strategic initiatives.
Requirements
- 10+ years of progressive hands-on technical experience in Artificial Intelligence, Machine Learning, Data Science, and Deep Learning.
- Demonstrated experience (3+ years) actively working on and deploying Generative AI and Agentic AI applications.
- Extensive hands-on experience with multiple AI and Agentic AI frameworks, such as (but not limited to): Generative AI: TensorFlow, PyTorch, Hugging Face Transformers, OpenAI API, LangChain, LlamaIndex, etc. Agentic AI: LangChain Agents, Auto-GPT, CrewAI, multi-agent simulation frameworks, etc.
- Experienced with leading LLM models such as OpenAI's series, Google's Gemini, Meta's Llama, and Anthropic's Claude, including fine-tuning and deployment for specific applications.
- Deep understanding and practical experience with Multi-Component Platforms (MCP) and Agent-to-Agent (A2A) communication patterns.
- Experience with cloud platforms (Azure, GCP, AWS) and MLOps practices.
- 5 + years of experience writing and deploying production quality models in languages such as Python
Responsibilities
- Provide thought leadership around applying AI and ML technology and help define technical direction and architecture with engineering team members.
- Leading the exploration and application of Large Language Models, Agentic AI and Generative AI, venturing into new areas within these fields.
- Architect and implement robust, scalable, and efficient AI systems leveraging a variety of AI/ML, data science, deep learning, and agentic AI frameworks.
- Drive the integration of complex Model Context Protocol (MCP) and agent-to-agent (A2A) communication protocols, ensuring seamless interaction and optimal performance.
- Design, build, and deploy autonomous agents capable of complex decision-making and task execution in dynamic environments.
- Design and implement scalable and efficient AI/ML systems, architectures, and pipelines that can handle large volumes of data and deliver accurate and timely results.
- Develop and maintain real-world NLP features using the latest techniques for call routing, intent identification, named entity recognition, information retrieval, summarization etc.
Other
- REMOTE FROM INDIA
- Regularly self-educate while mentoring and provide technical leadership to other engineers, fostering a culture of continuous learning and excellence.
- Collaborate closely with cross-functional teams including data scientists, software engineers and product managers to translate business requirements into technical solutions.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Outstanding written and verbal communication skills
