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Main Sail is seeking an experienced Lead AI Engineer, with expertise in context engineering and agent design who will develop AI solutions in Google, AWS and Microsoft ecosystems and will have the opportunity to mentor and lead AI engineers in the team. Responsibilities include building and (/or) mentoring AI engineers to build conversational agents, integrating with natural language processing or generative AI, and agents/ virtual assistants to software applications. AI Engineer is responsible for designing and delivering data access through APIs and ensuring that these solutions are securely deployed.

Core Responsibilities:

Developing applications that interact with web services, APIs, and other software applications.
Mentoring and leading AI design and development efforts as needed.
Conducting peer reviews for AI design and development efforts to ensure existing standards are adhered to and establish additional standards as needed.
Designing the overall structure of Agentic AI solutions, including determining necessary features, user flow, API development and integration with other systems. Requires understanding of API design principles and specific constraints of AI service interfaces.
Implementing and tuning Natural Language Processing techniques to improve AI assistants’ understanding and response accuracy.
Training and deploying AI models, and monitoring solution performance by creating and utilizing Dashboards.
Creating custom indexes, managing data sources, and tuning intent matches to improve accuracy and relevance of results within the AI solution context.
Designing conversational flows that provide a seamless and intuitive user experience, with strong focus on making the agent interactions as human-like and engaging as possible.
Analyzing agent interaction data to identify patterns, trends, and areas for improvement. Preparing reports on agent performance metrics.
Identifying and resolving issues related to agent performance, including debugging and updating the system as necessary.
Ensuring the AI agent/ conversational assistant complies with data privacy laws and maintaining high standards of security, especially when handling sensitive user data.
Working effectively with cross-functional teams, including business analysts, UX designers, project managers, and business customers and business SMEs from across the enterprise. Good communication skills are essential.
Collaborating effectively with Automation Center of Excellence (CoE) team members, incorporating the established standards; adhering to organization process and ensuring that solutions align with target architectures and technology roadmaps.
Ensuring that AI systems operate safely, transparently and within acceptable boundaries in alignment with the organization’s governance policies and practices.
Planning, initiating and spearheading proof of concept (POC) initiatives using emerging technologies.
Technical writing leveraging tools such as Word, PowerPoint, Visio, SharePoint, and Excel to develop presentations and white papers.

Skills & Credentials:

Extensive knowledge and experience developing AI Conversation agents using Google tools such as CX Agent Studio, Google Conversational Agents, Google Dialogflow CX, and(/or) Google CCAI Services is required.
Experience in creating and maintaining Enterprise Looker Dashboards for monitoring performance of implemented AI Agents is required.
Experience developing Generative AI solutions in AWS ecosystem including but not limited to AWS services such as AWS Bedrock, AWS Transcribe, AWS Comprehend, Lamda and Step Functions is required.
Ability to develop AI agents/ virtual assistants using Microsoft Foundry with Azure services like Azure AI Search, and Azure AI Language Service, Microsoft Power Platform and Microsoft CoPilot Studio.
Ability to integrate virtual assistants with various Microsoft services (such as Office 365, SharePoint) and third-party APIs to enhance functionality.
Deep understanding of API design principles and specific constraints of AI service interfaces.
Strong programming skills in languages such as C#, .NET, JavaScript, or Python. Experience in developing, testing, and deploying chatbot applications.
Ability to facilitate and lead discussions with business SME’s
Ability to create and present Ai solution proposals and communicate both business and technical concepts.
Ability to lead and conduct emerging technology analysis and conduct proof of concept initiatives.
Experience in training and deploying AI models.
Experience in leading efforts to create technology solutions and architectures impacting critical areas of the business.
Ability to establish and maintain a high-level of customer trust and confidence.
Ability to think critically and solve problems.
Strong consultative skills at a cross-functional level.

Education & Experience:

Bachelor’s degree in computer science, Information systems or related discipline, or equivalent and extensive related project experience; Master’s degree preferred.
Six years of experience in IT, with at least 4 years AI Conversational Agents and (or) Generative AI combined implementation experience using Microsoft, Google and AWS ecosystems.
2 years’ AI Engineer Experience developing Google conversational agents / CX Agent Studio / Dialogflow CX Web and Voice Virtual Assistants is mandatory.
2 years developing Enterprise Looker Dashboards to monitor AI Agent performance is mandatory.
2 years’ AI Engineer Experience in AWS ecosystems using AWS services such as AWS Bedrock, AWS Transcribe, AWS Comprehend, Lamda and Step Functions are mandatory.
Agentic AI Developer Experience using Microsoft Foundry is preferred.
Experience developing and maintaining SharePoint online solutions using MS Power Platform preferred.
Google and AWS Certifications relevant to this role preferred.
Minimum of six years of hands-on design and implementation experience in IT, with knowledge in a minimum of two of the following technical disciplines:
- Application development.
- Network design.
- Middleware.
- Servers and storage.
- Database management.
- Operations.

Artificial intelligence and machine learning fundamentals.
Natural language processing (NLP) and large language model (LLM) integration.

Requirements:

Bachelor’s degree in computer science, Information systems or related discipline, or equivalent and extensive related project experience - Required.
Six years of experience in IT, with at least 4 years AI Conversational Agents and (or) Generative AI combined implementation experience - Required 6 Years.
AI Engineer Experience developing Google conversational agents / CX Agent Studio / Dialogflow CX Web and Voice Virtual Assistants - Required 2 Years.
2 years developing Enterprise Looker Dashboards to monitor AI Agent performance - Required 2 Years.
AI Engineer Experience in AWS ecosystems using AWS services such as AWS Bedrock, AWS Transcribe, AWS Comprehend, Lamda and Step Functions - Required 2 Years.
Google and AWS Certifications relevant to this role preferred. - Highly desired.

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