Principal Software Engineer – Next-Generation API & AI Platform Architecture

SpyCloud•Austin, TX

About The Position

SpyCloud is on a mission to make the internet a safer place by disrupting the criminal underground. SpyCloud’s solutions thwart cyberattacks and protect more than 4 billion accounts worldwide. Cybersecurity is an exciting, evolving space, and being at the forefront of the fight to disrupt cybercrime makes SpyCloud a special place to work. If you’re driven to align your career with a fantastic mission, look no further! We are seeking a Principal Engineer to lead the hands-on architecture and development of our next-generation data and intelligence APIs. This role is deeply technical and execution-focused, responsible for defining API contracts, building production services, and architecting the platform interfaces high-performance throughput, agentic workflows, and external customer integrations. You will operate at the intersection of distributed systems, data platforms, and agentic orchestration, ensuring our APIs are scalable, governed, observable, and designed for long-term evolution. This role requires strong systems thinking, high-quality implementation standards, and the ability to translate platform strategy into production-grade services. This is a hands-on engineering role with architectural authority.

Requirements

10+ years of experience building distributed systems, APIs, or large-scale data platforms.
Deep experience designing and implementing customer-facing APIs as long-lived products.
Strong understanding of schema governance, versioning strategies, and contract design.
Experience productionizing ML models and exposing inference services.
Experience designing or integrating agentic or autonomous workflows.
Experience building service layers on top of systems of record or semantic data layers.
Strong background in distributed systems reliability, observability, and scalability.
Proficiency in Go & Python (and/or backend service languages).
Hands-on experience with Databricks/Snowflake
Strong experience with AWS infrastructure and infrastructure-as-code tools

Nice To Haves

AWS services including Redshift, S3, EC2, and related cloud-native tooling.
Data stores including Elasticsearch, PostgreSQL, Redis, and graph databases (e.g., Neo4j or AWS Neptune).
Experience building high-performance APIs and service layers over heterogeneous data systems.
Familiarity with Databricks/Snowflake and/or SageMaker is a plus.
Experience in cybersecurity, identity, fraud, or risk systems is a plus.

Responsibilities

Architect and implement customer-facing data and intelligence APIs with clear versioning, SLAs, and backward compatibility.
Define and enforce API contracts for:
Low latency, high throughput endpoints
Agentic workflows (tools, actions, state transitions, handoffs)
Context retrieval and enrichment
Design APIs as durable platform interfaces, not thin wrappers over storage systems.
Establish standards for schema governance, payload design, and service boundaries.
Architect service layers that support agentic workflows, including orchestration interfaces, guardrails, and runtime observability.
Build API surfaces that expose model outputs safely and consistently.
Collaborate with MLEs and Data Scientists to move models from experimentation into robust inference services.
Ensure proper lifecycle management, monitoring, and rollback mechanisms for ML-powered endpoints.
Design and implement service layers that sit on top of the gold-layer system of record.
Build and evolve context hubs derived from authoritative systems of record, enabling consistent entity, identity, or risk context for downstream services.
Ensure APIs are aligned with medallion architecture principles and platform data contracts.
Prevent fragmentation by maintaining strong coupling to canonical schemas and governed data models.
Design high-throughput, low-latency services supporting batch and streaming workloads.
Implement scalable infrastructure patterns on AWS.
Ensure strong observability, error handling, performance tuning, and cost awareness.
Drive infrastructure-as-code practices and production readiness standards.
Serve as a senior architectural voice in design reviews.
Raise the bar on code quality, system design, and operational rigor.
Mentor engineers on API design, distributed systems, and ML integration patterns.
Influence platform direction through technical depth rather than organizational authority