Senior Manager – AI Engineer

This is a fully remote position, open to applicants in Connecticut.

📋 Description

• Articulate the technical vision and architecture for AI and ML solutions, encompassing LLM-based applications, conversational voice AI, chatbot platforms, and AI-enhanced BI systems.

• Supervise the development of training data pipelines and datasets for fine-tuning, evaluation, and inference on an enterprise scale.

• Establish enterprise standards for monitoring model performance, detecting drift, retraining, and lifecycle governance.

• Propel the implementation of vector embeddings, semantic search, and AI orchestration frameworks.

• Provide engineering leadership for backend services (APIs, microservices) to enable scalable AI capabilities throughout the enterprise.

• Oversee the creation of scalable data pipelines that support ingestion, transformation, and real-time inference workloads.

• Facilitate the integration of AI capabilities into enterprise platforms, including customer-facing voice and chat systems as well as internal analytics environments.

• Ensure that solutions comply with enterprise standards for scalability, reliability, performance, and security.

• Define and govern model lifecycle management practices, including versioning, deployment, rollback, and compliance.

• Lead the development of enterprise AI platforms and infrastructure for model hosting, orchestration, and scaling.

• Establish CI and CD standards along with deployment frameworks for AI systems across engineering teams.

• Build and manage observability layers to monitor system performance, model behavior, and operational health.

• Set the direction for AI safety and responsible AI practices, including guidelines for bias mitigation, hallucination reduction, and policy compliance.

• Formulate and advance the enterprise AI strategy in alignment with the technology vision, platform evolution, and long-term organizational objectives.

• Lead alignment across a complex, matrixed organization, influencing engineering, product, analytics, and business leadership.

• Act as a trusted advisor to executive leadership, articulating AI strategy, technical trade-offs, risks, and business impacts.

• Own the AI investment strategy, including prioritization, funding alignment, and resource allocation across various initiatives.

• Accelerate enterprise-wide AI adoption by establishing scalable enablement models across engineering and business teams.

• Define and execute capability enhancement strategies, including upskilling engineers, promoting best practices, and facilitating self-service AI development.

• Champion innovation by introducing emerging AI technologies, tools, and solution patterns to expedite experimentation and delivery.

• Establish and govern AI vendor and partner strategy, including evaluation, selection, negotiation, and performance oversight.

• Oversee SOW development and collaborate with product and finance leadership to manage budgets, forecasts, and investment planning.

• Serve as the primary liaison between engineering and executive leadership, ensuring transparency, accountability, and successful delivery outcomes.

• Influence enterprise architecture, engineering standards, and AI governance frameworks.

⛳️ Requirements

• Extensive experience in leading engineering or AI and ML organizations within large-scale enterprise settings.

• Demonstrated ability to function at a senior leadership level, influencing executive stakeholders and enterprise strategy.

• Proven track record in owning or driving technology investment strategy, budgeting, and resource allocation.

• Experience in spearheading transformation initiatives and promoting the adoption of emerging technologies across organizations.

• Background in building and scaling engineering platforms, systems, or organizational capabilities.

• Experience within healthcare, health insurance, or regulated healthcare environments, with a strong grasp of compliance, data privacy, and domain-specific challenges.

• Deep expertise in software engineering fundamentals (SDLC, architecture, distributed systems design).

• Proficiency in one or more programming languages (Python, C#, Java, etc.).

• Experience in building data pipelines and working with both structured and unstructured data.

• Hands-on experience with AI and ML frameworks, platforms, or applied AI systems.

• Strong understanding of APIs, microservices, and cloud-based architectures.

• Experience with cloud platforms (Azure, AWS, or GCP).

• Familiarity with databases (SQL / NoSQL).

• Experience in leading vendor strategy, including evaluation, selection, and delivery governance.

• Experience in defining or leading enterprise AI strategy or platforms at scale (Preferred).

• Hands-on experience with LLMs, prompt engineering, or fine-tuning models (Preferred).

• Experience in constructing conversational AI (voice and chat) ecosystems (Preferred).

• Experience with AI-augmented analytics or business intelligence platforms (Preferred).

• Experience with vector databases, embeddings, and semantic search (Preferred).

• Familiarity with MLOps, observability, and model monitoring frameworks (Preferred).

• Experience in implementing responsible AI, governance, and risk management practices (Preferred).

• Experience operating at Director or VP level or equivalent leadership scope (Preferred).

• Experience in healthcare, analytics, or enterprise data platforms (Preferred).

• Exposure to tools such as Databricks, Spark, or real-time analytics systems (Preferred).

🏝️ Benefits

• Medical, dental, and vision coverage.

• Paid time off.

• Retirement savings options.

• Wellness programs.

• Comprehensive benefits package.