april
AI
Hands-onAI&DataEngineeringManager
Neural analysis suggests this role is
optimal for Manager candidates.
“Hands-on AI & Data Engineering Manager at april. Skills: AI Engineering, Data Engineering, Engineering Management, LLM Systems, Production Deployment. Lead a team of data scientists, data engineers and product analysts. Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation”
What You'll Achieve.
ensure that AI capabilities—from LLMs and agents to product data insights—are translated into reliable, scalable production systems; responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes; ensure AI solutions are safe, scalable, observable, and continuously improving; improve accuracy, UX, and business impact; Drive alignment between AI capabilities and measurable product outcomes
Industry & Context.
analyzing product data and user behavior to continuously improve AI performance and product outcomes; Analyze user interactions with product features to improve accuracy, UX, and business impact; Translate product and business goals into technical roadmaps and execution plans; Drive alignment between AI capabilities and measurable product outcomes
What They're Looking For.
Must Have
6+ years of software engineering experience building production-level systems, 2+ years of engineering management or technical leadership experience, experience building large-scale backend systems in Python, Experience developing modern web applications using frameworks such as React / Next / Angular / Vue, Experience deploying and operating LLM-based systems in production, including evaluation and iteration, understanding of data pipelines, experimentation, and product analytics, Experience with modern cloud environments such as Google Cloud Platform or Amazon Web Services, Passion for clean code, scalable architectures, and data-driven product development, Experience with prompt engineering, RAG architectures, and vector databases, Experience building AI agents or autonomous workflows
Nice to Have
Experience with frameworks such as ADK, A2A, LangChain, LangGraph, or LlamaIndex or equivalent, Experience with gRPC and protobuf-based architectures, Experience building MCP servers, Background in data engineering, experimentation platforms, or ML infrastructure
What You'll Do.
Lead a team of data scientists
data engineers and product analysts
Own the delivery of AI-powered product capabilities
from research and experimentation to production and operation
and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs
and intelligent workflows into core consumer experiences
Ensure AI solutions are safe
and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring
and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes
How You'll Work.
Team & Collaboration
work closely with data scientists, product managers, and designers; Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Process & Methodology
Translate product and business goals into technical roadmaps and execution plans
Full Job Description
ABOUT THE ROLE We’re looking for a hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities—from LLMs and agents to product data insights—are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making. RESPONSIBILITIES - Lead a team of data scientists, data engineers and product analysts. - Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation. - Drive excellence, code quality, and best development practices. - Provide technical direction and hands-on guidance for complex AI systems. - Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences. - Ensure AI solutions are safe, scalable, observable, and continuously improving. - Lead initiatives around product data analysis and experimentation. - Analyze user interactions with product features to improve accuracy, UX, and business impact. - Partner with product teams to define metrics, dashboards, and experiments that guide product improvements. - Design system architectures for AI-enabled applications at scale. - Evaluate and select technologies for AI platforms and data pipelines. - Guide the development of prompt engineering frameworks and centralized prompt management. - Ensure robust monitoring, evaluation, and feedback loops for AI outputs. - Translate product and business goals into technical roadmaps and execution plans. - Drive alignment between AI capabilities a
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