Hands-on AI & Data Engineering Manager

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 and measurable product outcomes.

Requirements

6+ years of software engineering experience building production-level systems.

2+ years of engineering management or technical leadership experience.

Strong 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.

Strong 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.

About april

april is the only embedded, year-round tax platform built to power smarter financial decisions. From filing to planning to onboarding, april’s white-labeled tools bring real-time tax intelligence into the platforms people already use, helping users understand the impact of every paycheck, equity transaction, or income shift, and stay on top of tax payments throughout the year. Built to handle even the most complex tax situations, april’s AI-powered tax engine ingests data directly from partner apps to deliver accurate outcomes in record time—making tax planning and filing more connected, contextual, and accessible than ever. With API-first infrastructure and seamless data integrations, april helps partners deliver more value, deepen loyalty, and turn taxes into a strategic edge—for their clients and their business.