Senior Engineering Manager - AI Engineering - Applied AI

About the Role

Key Responsibilities

• Lead a team of talented engineers by fostering aligned autonomy, offering technical guidance, and supporting performance and career development.
• Translate product and business requirements into technical roadmaps, sprint planning, and delivery schedules that align with FICO's broader AI strategy.
• Drive the design and implementation of cutting-edge AI solutions, overseeing Agentic workflows (e.g., tool-using agents), RAG architectures, and custom fine-tuning and evaluation frameworks to ensure high performance and reliability.
• Ensure high-quality code and scalable architectures for LLM-based services and workflows; dive deep into code and contribute hands-on to key features and critical fixes.
• Implement systems for continuous AI app evaluation, A/B testing, backtesting, and drift detection to sustain high accuracy and relevance of deployed AI features over time.
• Work closely with UX designers to refine user experience, partner with product teams to prioritize features, and engage with other engineering leaders to align AI capabilities across the platform.
• Drive engineering best practices around testing, observability, documentation, and compliance, especially in AI governance and auditability.
• Own service reliability and operational excellence, ensuring systems meet agreed-upon SLOs and respond well to scale and production demands.

Requirements

• 10-15 years of industry experience in software, machine learning, or data engineering, with a proven track record of leading complex, large-scale projects and making strategic technical decisions.
• Solid experience in software engineering, with at least 2+ years in a people management or technical leadership role.
• Proven track record of delivering backend or data-intensive systems in production, preferably involving AI/ML.
• Hands-on experience with one or more of: Python, Go, Java, and familiarity with data infrastructure (e.g., Kafka, Spark, SQL/NoSQL, object stores).
• Strong understanding of cloud infrastructure and containerization (AWS, GCP, or Azure; Docker; Kubernetes).
• Experience collaborating with ML teams to productionize models or workflows (LLMs, RAG, evaluation pipelines is a plus).
• Comfortable working across the stack, from system architecture to API design to debugging complex production issues.
• Excellent communication and organizational skills, with the ability to align technical direction with product and business priorities.
• Passion for team building, continuous improvement, and fostering a positive, inclusive engineering culture.
• Strong ability to mentor and develop high-performing engineering teams, fostering collaboration across departments to deliver impactful solutions.
• Proven success in fast-paced, high-growth environments, with the agility to adapt and drive results in high-stakes settings.
• Demonstrated experience in applying Large Language Models (LLMs) to address real-world challenges effectively.
• Bachelor's or Master's degree in Computer Science or a related field, preferably with a specialization in Machine Learning or AI.

Nice to Have

• Experience with evaluation pipelines for AI models.
• Experience with AI governance and auditability practices.

Qualifications

• Bachelor's or Master's degree in Computer Science or a related field, preferably with a specialization in Machine Learning or AI.

Benefits & Perks

• Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.
• An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.
• The targeted base pay range for this role is: $137,000 to $215,000.