Overview

Instacart’s Fraud, Appeasement & Identity (FAI) team protects the marketplace and everyone who depends on it—customers, shoppers, retailers, and brand partners. We build the systems that detect and prevent fraud across payments, accounts, and promotions; ensure that refunds and appeasements are fair, accurate, and resistant to abuse; and verify identity so that every transaction can be trusted. Our mission is to safeguard revenue and customer trust while keeping friction low, so the business can scale with confidence.

We’re looking for a Senior Software Engineer to serve as a technical leader across FAI. In this role, you’ll define the technical strategy and architecture for critical trust surfaces real-time fraud detection, risk decisioning, appeasement and refund-abuse controls, and identity and account-verification workflows. You’ll partner closely with Product, Data Science and ML, Design, Fraud Operations, Legal, and external identity and risk vendors to deliver fast, safe, and scalable solutions.

This is a high-impact role where your work directly influences fraud losses, customer trust, marketplace integrity, and our ability to scale sustainably while meeting regulatory and privacy standards. If you thrive in fast-moving, highly cross-functional environments and enjoy rolling up your sleeves to solve adversarial problems at scale, you’ll feel right at home here. We go far together, communicate with candor, and prioritize solutions where everyone can win.

About the Job

• Design, build, and operate significant components of FAI systems end to end—fraud detection, risk decisioning, appeasement/refund-abuse controls, and identity verification— delivering reliable, safe features as the platform scales to millions of customers and shoppers.
• Contribute to the design of real-time and near-real-time risk decisioning systems that balance detection quality with customer experience, minimizing both fraud losses and false positives on good users.
• Deliver business-critical trust initiatives (e.g., account-takeover prevention, payment and promo-abuse defense, appeasement-abuse controls, identity and eligibility verification), building auditable, privacy-first systems with strong observability and SLAs
• Partner with Data Science and ML to productionize fraud and risk models—owning feature pipelines, model-serving infrastructure, and the feedback loops that keep detection effective against evolving adversaries.
• Run large, cross-functional programs across multiple engineering and business teams; translate ambiguous, adversarial problem spaces into crisp technical plans, manage risk and dependencies, and unblock execution.
• Mentor and develop engineers through design reviews, high-quality code practices, and clear technical standards; raise the technical bar and cultivate the next generation of technical leaders on the team.
• Drive AI-first patterns into how the team builds - embedding AI and agentic automation into development procedures, code review, and operational runbooks, and establishing the standards and guardrails that let the team ship faster without compromising safety.
• Champion the use of AI to strengthen detection itself - applying ML and LLM-based approaches to fraud, risk, and identity signals, and building the tooling and feedback loops that keep these systems effective against evolving adversaries.
• Continuously improve the reliability, latency, and cost efficiency of trust services; establish and enforce SLOs, drive incident learnings, and champion secure-by-default, AI-augmented development workflows.

About You

Minimum Qualifications

• 5+ years of software engineering experience building and operating large-scale distributed systems, high-traffic services, or real-time decisioning platforms.
• 2+ years owning end-to-end architecture and technical strategy for a domain or product area, from design through production operations.
• Experience collaborating across teams and functions to ship cross-functional work
• Proficiency in one or more backend languages (e.g., Go, Java, Python) and with modern cloud infrastructure (e.g., AWS or GCP) and data stores (e.g., Postgres, DynamoDB, Clickhouse, Redis).
• Experience designing low-latency, high-availability systems that make automated decisions in the request path (e.g., risk scoring, rules/policy engines, or eligibility checks).
• Experience designing systems involving sensitive data identity, payments, personal information, or similar with strong privacy and security best practices and auditability.
• Hands-on experience applying AI and agentic automation to engineering workflows and a point of view on how to embed AI-driven patterns into how a team builds and operates.
• Demonstrated mentorship and team development experience, including leveling up engineers through design guidance and rigorous code reviews.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Direct experience with trust & safety, fraud, risk, identity/KYC, payments, or abuse-prevention systems in a high-scale marketplace or platform.
• Experience partnering with Data Science/ML to deploy and operate models in production—feature stores, real-time inference, monitoring, and retraining loops.
• Experience partnering with Legal/Policy on compliance-related work and navigating evolving regulatory requirements; familiarity with audit trails and policy engines.
• Background in evaluating, integrating, and managing third-party identity, payments, or risk vendors; establishing technical SLAs; and executing zero-downtime migrations and fallback strategies.
• Experience with experimentation platforms and analytics to measure detection quality, false-positive rates, and impact on customer experience.
• Experience in marketplace, logistics, fintech, rideshare, or gig-economy environments.

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