Engineering Manager

As a member of the Engineering leadership team at Conservice, you will be responsible for leading the AI Platform team at Conservice. This position will be leading the AI innovations within the company and working with other teams and business partners to implement AI solutions to solve business problems. This position will also involve leading, mentoring, growing and building a highly-effective Software Engineering team within an Agile environment.

• Lead discussions with your team about emerging AI/ML tools, technologies, frameworks, and processes that may impact how our organization grows and evolves, including LLMs, vector databases, AI orchestration platforms, and MLOps practices.
• Your primary goal will be to enable the software development teams across Conservice to turn AI concepts into production-ready solutions and ensure consistent delivery of high-quality, scalable, innovative AI-powered features with the AI management platform.
• As an Engineering Manager, you are a dynamic leader who drives an AI engineering team to new heights each and every day.
• You will work closely with Product Management and other technical leaders to stay ahead of the curve with our AI products, model architecture, and platform capabilities.
• You will be responsible for AI/ML engineering craftsmanship and best practices on your team, including responsible AI principles, model governance, monitoring strategies, and continuous improvement of AI systems.
• Manage an Agile process that consistently delivers quality AI products to Conservice's team members and customers while balancing experimentation with production reliability.
• Rally your team to make and keep commitments to customers, the business, and themselves, understanding the unique challenges of AI development timelines and iterative model improvement.
• Team up with your Product Owner in planning and preparing your team's backlog, including AI experimentation, model training cycles, and production deployment priorities.
• Ensure the quality craftsmanship of your team's AI/ML engineers, including proper model evaluation, testing strategies for AI systems, monitoring for model drift and performance degradation, and scalable inference architecture.
• Meet with your team to ensure their path for success is clear and we're instilling behaviors that balance innovation in AI with responsible deployment and ongoing system maintenance.
• Mentor, coach, and assist team members to be productive AI/ML engineers contributing to Conservice's utility management platform, helping them grow in areas like prompt engineering, model fine-tuning, RAG architectures, and AI system design.
• Participate in interviews to find the next great AI engineer or leader at Conservice.
• Establish and track key performance indicators (KPIs) for the AI Platform, focusing on things like adoption rate, model service latency, inference cost optimization, and overall production reliability.

Qualifications

Technical Requirements:

• Knowledge of AI/ML technologies and architectures including: LLM integration and deployment, vector databases (Pinecone, Weaviate, Chroma), RAG (Retrieval-Augmented Generation) systems, model serving platforms, and AI orchestration frameworks (LangChain, LlamaIndex, etc.)
• Experience with the Conservice technology stack as it applies to AI systems: Microservices, .NetCore, C#, React, SingleSpa, PostgreSQL, Azure AI services, Docker, ML pipelines, AI model deployment, data pipelines, and real-time inference systems.
• Understanding of MLOps practices including model versioning, A/B testing for models, monitoring and observability for AI systems, and CI/CD for machine learning.
• Familiarity with responsible AI practices, bias detection and mitigation, model explainability, and AI governance frameworks.
• Demonstrate and drive the adoption of advanced knowledge of AI/ML engineering practices, including experiment tracking, model evaluation metrics, prompt engineering strategies, and testing methodologies for non-deterministic systems.
• Established track record of being the go-to person for AI/ML initiatives, able to navigate both the technical complexities and organizational change management required for AI adoption.
• Experience optimizing AI development processes including experimentation workflows, model training pipelines, and deployment strategies to ensure efficient iteration and production reliability.
• Strong communication skills with the ability to explain AI