AI Application Engineer

Job Description

We are seeking a highly experienced and visionary Lead AI Application Engineer to join our core AI team. This pivotal role will be instrumental in designing, developing, and deploying advanced Generative AI and Agentic AI applications. You will be a key contributor to our strategic initiatives, working on complex problems that require deep technical expertise and a forward-thinking approach. This is an exceptional opportunity for an individual who thrives on building sophisticated, autonomous AI systems and wants to make a significant impact.

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.
• Conduct extensive research and experimentation with emerging AI technologies, specifically in Generative AI and Agentic AI, to identify and implement innovative solutions.
• Collaborate closely with cross-functional teams including data scientists, software engineers and product managers to translate business requirements into technical solutions.
• Regularly self-educate while mentoring and provide technical leadership to other engineers, fostering a culture of continuous learning and excellence.

Requirements

Qualifications

• 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 GPT 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
• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.

Knowledge, Skills, And Abilities

• Expertise in developing on a Azure cloud platform is a big plus
• Contributions to open-source AI projects, particularly in Generative AI or Agentic AI
• Familiarity with reinforcement learning and multi-agent reinforcement learning.
• Outstanding written and verbal communication skills.