Engineering Manager, Data / AI

Brightside

About The Position

You’ll lead a high-impact team at the core of our data, AI, and intelligence platforms, building the intelligence layer behind internal tools and client-facing AI experiences - from conversation intelligence to data models and LLM agents. This is a hands-on leadership role requiring strength across people management, architecture, coding, and cross-functional alignment. You bring deep experience in Python, TypeScript, data systems, and production AI workflows. You’ll scale a critical area of the business - coaching engineers, setting technical direction, and partnering across teams to turn ambitious ideas into real systems. Most importantly, you’ll lead AI engineering by example, building practical solutions that drive meaningful productivity gains through intelligent automation. This is not a purely managerial or maintenance role. You’ll actively contribute to code and help define how modern AI systems are built and deployed across the organization... shaping a core part of our technical future.

Requirements

8+ years building and scaling production software systems
2+ years managing and leading engineers
Strong proficiency in Python, TypeScript, and backend development
Experience designing distributed systems, APIs, and data-intensive applications
Hands-on experience building production AI systems, agents, or automation workflows
Solid understanding of LLMs, APIs, and tool integration patterns
Experience with data platforms (lakes, warehouses, pipelines) and AWS/cloud-native systems
Strong problem-solving, debugging, and rapid prototyping skills
Comfortable contributing in code while leading a team
Strong communication skills and ability to operate in fast-paced environments

Nice To Haves

Experience with multi-agent systems or workflow automation platforms
Track record of improving engineering productivity through AI or automation
Experience evaluating AI system performance, reliability, and quality
Familiarity with modern AI development practices and tools
Experience with Databricks, DBT, or modern data platforms
Knowledge of event-driven architectures, orchestration, and observability
Startup or high-growth environment experience

Responsibilities

Lead, hire, and develop a high-performing Client Intelligence engineering team
Drive clarity, accountability, and predictable delivery across multiple initiatives
Foster a culture of ownership, engineering excellence, and continuous improvement
Coach engineers through hands-on guidance, feedback, and career development
Design and build AI agents and workflows that automate complex processes and improve productivity
Identify bottlenecks and deploy AI-driven solutions to reduce manual work
Establish best practices for agent orchestration, tool integration, prompt design, evaluation, and observability
Promote adoption of modern AI engineering practices across the organization
Own technical direction for client intelligence systems, AI workflows, and supporting data architecture
Design scalable, maintainable, and observable systems across Python services, data pipelines, and agent-based architectures
Set and uphold high standards for development, testing, and operational excellence
Balance speed and rigor to enable rapid, reliable delivery
Contribute to code in Python, TypeScript, and backend systems
Build and scale production-grade AI services and workflows
Review code, improve quality, and troubleshoot complex technical issues
Rapidly prototype and evolve solutions into stable production systems
Partner with data teams on data lake strategy, modeling, governance, and reliability
Ensure clean, well-structured data supports AI workflows and product experiences
Maintain strong architectural discipline around shared data assets
Translate ambiguous business goals into clear engineering plans with cross-functional partners
Communicate tradeoffs, risks, and priorities effectively
Align engineering execution with product strategy and business impact