Forward deployed engineer - AIS job opportunity at Weekday AI.

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Date2026-02-12T03:31:05.431Z bot
Weekday AI Forward deployed engineer - AIS
Experience: General
Pattern: Full-time
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This role is for one of the Weekday's clients Location: Remote (India) JobType: full-time We are seeking a Forward Deployed Engineer – AIS to work at the intersection of engineering, customer success, and applied AI solutions. In this role, you will act as a technical partner to customers, deploying, customizing, and optimizing AI-driven systems in real-world environments. You will bridge the gap between product engineering and client requirements, ensuring seamless implementation and measurable business impact. Key Responsibilities Deploy and integrate AI/Intelligent Systems (AIS) solutions into customer environments, ensuring reliability, scalability, and performance. Customize and configure solutions based on client-specific workflows, data structures, and operational needs. Collaborate with cross-functional teams including product, engineering, and data science to provide feedback from field implementations and influence product improvements. Design and build integration layers, APIs, and automation workflows to connect AIS platforms with customer systems. Troubleshoot technical issues across the stack, including infrastructure, data pipelines, and application layers. Optimize system performance, ensuring low latency, high availability, and secure operations. Conduct technical discovery sessions with customers to understand requirements and define implementation strategies. Develop technical documentation, implementation guides, and best practices to support scalable deployments. Ensure data integrity, security, and compliance standards are maintained during deployments. Provide post-deployment support, monitoring, and continuous improvement of deployed systems. What Makes You a Great Fit Strong software engineering background with hands-on experience in Python or similar programming languages. Experience working with APIs, microservices architecture, and system integrations. Familiarity with AI/ML systems, data pipelines, or intelligent automation platforms. Solid understanding of cloud environments (AWS, Azure, or GCP) and containerization tools such as Docker or Kubernetes. Experience working directly with customers in technical implementation or solution engineering roles. Ability to debug complex issues across infrastructure, application, and data layers. Strong knowledge of SQL and data modeling principles. Comfortable working in a remote, distributed team environment while managing multiple deployments simultaneously. Excellent communication skills with the ability to translate technical details into business value. Proactive mindset with strong ownership and accountability for outcomes.

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