Role Description As a Senior Lead Software Engineer, you will be at the forefront of our AI initiatives, leading the design, development, and implementation of cutting-edge AI solutions. You will work closely with cross-functional teams to drive innovation and ensure the successful delivery of AI projects. Your expertise will be crucial in shaping the future of our AI capabilities and driving business value through advanced technologies. This role is designated as a fully remote position within the United States. Main Responsibilities - AI Solution Development: Lead the end-to-end design, development, testing, deployment, and ongoing support of sophisticated conversational AI solutions. - Project Leadership: Oversee AI projects from conception to deployment, ensuring timely delivery and alignment with business objectives. - Collaboration: Work closely with data scientists, software engineers, and business stakeholders to understand requirements and deliver AI solutions that meet their needs. - Innovation: Stay up to date with the latest advancements in AI and machine learning and apply this knowledge to drive continuous improvement and innovation within the team. - Mentorship: Provide technical guidance and mentorship to junior AI engineers, fostering a culture of learning and growth. - Performance Optimization: Optimize AI models for performance, scalability, and reliability, ensuring they meet the highest standards of quality. - Documentation: Create and maintain comprehensive documentation for AI models, algorithms, and processes to ensure transparency and reproducibility. - Integration: Integrate conversational agents seamlessly with backend APIs, databases (like Firestore), CRM systems, and other enterprise platforms within the GCP ecosystem. - Advanced Capabilities: Explore and implement advanced capabilities, potentially including Generative AI features available through Agent Builder and Vertex AI, to enhance conversational intelligence. - MLOps/AIOps Practices: Establish and maintain comprehensive MLOps/AIOps practices for conversational AI models on GCP, encompassing model monitoring, continuous integration/delivery (CI/CD), versioning, scalability, and robust alerting. - System Health Monitoring: Design and implement systems to collect, analyze, and leverage IT telemetry data and logs (using tools like Google Cloud Monitoring/Logging) for proactive alerting and monitoring of AI system health, performance, and potential issues. - Performance Metrics: Analyze and optimize conversational AI solutions for key performance metrics including latency, accuracy, user satisfaction, operational cost, and reliability on GCP. - Knowledge Sharing: Mentor junior engineers, share knowledge, and contribute to establishing best practices for conversational AI development within the organization. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a closely related technical field. - Minimum of 7 years of professional software engineering experience, with at least 4 years specifically focused on developing and deploying AI/ML solutions. Technical Skills - Python Programming - Dialogflow (CX/ES), Agent Builder, Conversational Agents - Google Cloud Platform (GCP) - Core AI/ML Concepts - Familiarity with Copilot Studio and Google ADK development - Generative AI (Preferred) - Vertex AI (Preferred) - Firestore, BigQuery (Preferred) - MLOps/AIOps (Preferred) - Backend API Integration - Familiarity with building agentic systems Non-Technical Skills - Team Leadership - Cross-Functional Collaboration - Strong Communication - Problem-Solving - Strategic Thinking - Responsible AI (Familiarity) - Strong analytical and problem-solving skills, with the ability to translate complex business requirements into AI solutions. - Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and present technical concepts to non-technical stakeholders. - Demonstrated leadership abilities, with experience in mentoring and guiding junior engineers. - A deep passion for AI and a commitment to staying current with the latest industry trends and advancements. Preferred Qualifications - Experience contributing to or utilizing an integrated Generative AI platform on GCP designed to streamline the end-to-end lifecycle of AI applications, from development and experimentation to robust deployment and monitoring. - Hands-on experience with key components of modern AI/ML infrastructure and data stacks within the Google Cloud ecosystem, specifically including Vertex AI Vector Search, Firestore, Vertex AI Model Registry, and BigQuery. Compensation This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors. - $105,786 - $141,047 in states: AL, AR, AZ, FL, GA, IA, ID, IN, KS, KY, LA, ME, MO, MS, MT, ND, NE, NM, OH, OK, PA, SC, SD, TN, UT, VT, WI, WV, WY - $111,074 - $148,099 in states: CO, HI, MI, MN, NC, NH, NV, OR, RI - $116,364 - $155,152 in states: AK, CA, CT, DC, DE, IL, MA, MD, NJ, NY, TX, VA, WA Benefits - Comprehensive package featuring a broad range of Health, Life, Voluntary Lifestyle benefits and other perks that enhance your physical, mental, emotional and financial wellbeing.