Lead the technical design and implementation of AI-powered product features from concept through production.
Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration.
Make pragmatic decisions to accelerate delivery while maintaining system integrity.
Ensure AI solutions are secure, observable, scalable, and aligned with platform standards.
Act as the technical lead for a cross-functional AI Pod.
Break down product requirements into executable technical workstreams and prototypes.
Guide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness.
Review code, architecture, and technical decisions to maintain quality and velocity.
Partner closely with Product Management to shape problem definitions, success metrics, and delivery plans.
Collaborate with the Data Science Leader to integrate models, analytics, and data assets into product workflows.
Translate data science outputs into consumable APIs, services, and product features.
Provide technical feedback on feasibility, scope, and tradeoffs during product discovery.
Ensure features are production-grade, including monitoring, logging, and performance tracking.
Implement guardrails around AI usage, including reliability, latency, cost controls, and failure modes.
Support experimentation frameworks, A/B testing, and post-launch learning loops.
Drive responsible AI practices, including explainability, bias awareness, and data privacy considerations.
Define and enforce lightweight engineering standards for AI-enabled systems.
Promote reuse of components, prompts, pipelines, and services across AI initiatives.
Mentor pod engineers on AI-adjacent system design and best practices.
Contribute to internal documentation and shared AI patterns/playbooks.

Requirements

BS or MS in Computer Science, Engineering, or related technical field.
5+ years of software engineering experience, including leading complex systems.
Strong experience designing and building production APIs and backend services.
Proficiency in Python and at least one backend language (e.g., Java, Node.js, Go).
Experience with cloud-native architectures (AWS, GCP, or Azure).
Solid understanding of data pipelines, model serving, and system observability.
Ability to work closely with product teams in fast-moving, iterative environments.

Benefits

Flexible work arrangements
Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI solutionsdata flowsmodel integrationAPIsapplication integrationproduction APIsbackend servicesPythoncloud-native architecturesdata pipelines

Soft Skills

leadershipcollaborationmentoringdecision makingproblem solvingcommunicationiterationfeedbackexperimentationadaptability

Certifications

BS in Computer ScienceMS in Computer ScienceEngineering degree