Software Engineer

We are seeking a strategic and technically-grounded Senior AI Product Analyst to drive the evolution of our Artificial Intelligence capabilities. This role sits at the intersection of product strategy and technical execution, requiring a professional who understands the full AI/ML Lifecycle—from raw data management to robust model governance.

The ideal candidate will bridge the gap between business needs and technical feasibility, specifically focusing on the deployment of Generative AI and Predictive AI solutions within high-scale cloud environments.

### Key Responsibilities

• Product Strategy & Ownership: Act as the Technical Product Owner for AI initiatives, defining roadmaps for GenAI and Predictive AI platforms, APIs, and cloud-native solutions.

• Lifecycle Management: Oversee the end-to-end AI/ML lifecycle, including data strategy, feature engineering, model training, and continuous deployment (CI/CD).

• Monitoring & Governance: Implement rigorous model observability and risk controls to ensure AI solutions remain performant, ethical, and compliant with enterprise standards.

• Cross-Functional Leadership: Partner with data scientists and engineers to translate business requirements into technical specifications for Docker, Kubernetes, or OpenShift environments.

• Cloud Orchestration: Navigate and utilize public cloud infrastructures (GCP or Azure) to scale AI services and manage containerized workloads.

• Technical Analysis: Conduct deep-dive analysis on model performance and user feedback to iterate on product features and improve predictive accuracy.

### Technical Requirements

• AI Solutions Expertise: 4+ years of experience delivering Artificial Intelligence solutions (GenAI or Predictive AI) in a professional or enterprise environment.

• Product/Solution Management: 2+ years of experience in product ownership or program delivery, specifically managing AI/ML platforms and APIs.

• The AI Lifecycle: 2+ years of hands-on experience in:

  • Data management and feature engineering.

  • Model deployment and monitoring/observability.

  • Model governance and risk management.

• Cloud & Infrastructure: 2+ years of experience with Google Cloud Platform (GCP) or Microsoft Azure, including container orchestration (Docker, Kubernetes, or OpenShift).

• Programming (Good to Have): Proficiency in Python for data analysis, scripting, or interacting with ML frameworks.

### Qualifications

• Demonstrated experience in Enterprise Functions Technology or high-scale platform delivery.

• Ability to communicate complex technical AI concepts to non-technical stakeholders clearly.

• Strong analytical mindset with a focus on "Product Thinking"—balancing user needs with technical scalability.

• Proven track record of managing model risk and ensuring the "safety" of GenAI outputs.