Chief Software Engineering Architect

DataStealth•Mississauga, ON

2d•Hybrid

About The Position

The Chief Software Engineering Architect is the most senior technical role at DataStealth. This role owns the overall technical strategy, architecture, and engineering standards for the entire DataStealth DSP platform. The architect will lead the technical direction of the company's most senior engineering cohort, including Principal and Distinguished Engineers. This is a hands-on role, with expectations to write production code approximately 30-50% of the time. Responsibilities include writing difficult components, leading applied research and experimental development, and prototyping designs. The role involves providing technical leadership, design review, unblocking, and architectural guidance to senior engineers, operating more as a principal technical lead than a traditional engineering manager. The position is based in Mississauga with a hybrid schedule (4 days in-office per week) and involves direct collaboration with the CTO and executive team on multi-year technical strategy, as well as with senior engineers on critical code. This role is responsible for defining the standard of technical excellence at DataStealth.

Requirements

15+ years of professional software engineering experience, with at least the last 5 in the most senior IC technical role at your organization (Chief Architect, Distinguished Engineer, Technical Fellow, Principal Architect, or equivalent)
Demonstrated hands-on coding at the most senior level—you have shipped production code in a Chief Architect or Distinguished Engineer role, not just approved designs. Expect to discuss specific systems you personally built and projects you personally de-risked through experimental development
Deep expertise in Java and JVM languages (required) plus at least two of TypeScript/Node.js, Golang, or Rust, with demonstrated ability to move fluently between them
Deep experience building security products—data security, tokenization, encryption, key management, DLP, CASB, EDR, or equivalent. You are a strong applier of cryptography: you know which primitives, libraries, and patterns to use, have designed systems around key hierarchies and HSMs, and have shipped systems under PCI-DSS, SOC 2, or equivalent regulatory scrutiny. You do not need to be a cryptographer, but you must know how to build secure systems with crypto correctly
Firsthand experience applying AI/ML to security problems in production—not AI-adjacent, not exploratory. You have designed and shipped at least one of: ML-based classification/detection, LLM-based analyst augmentation, agentic security automation, or adversarial ML defense. You have clear opinions on the current state of AI in the security product landscape and where it is going
Proven ability to lead Principal and Distinguished Engineers through technical credibility rather than authority—RFCs, design reviews, exemplar code, and technical vision documents
Comfort leading a small group of senior ICs as a technical lead in a shared-management model—light people-management load, high technical-leadership load
Deep experience designing and operating distributed systems at production scale—resilience, observability, performance, multi-region, cost—including at least one major cloud provider at depth and working command of the others
Track record of de-risking the hardest projects through applied research, prototyping, and experimental development
Strong grasp of networking fundamentals (HTTP/S, TLS, SSH, DNS, TCP/IP), Linux systems, and how they compose in distributed systems
Deliberate, quality-driven use of agentic AI coding tools (Claude Code, Copilot, Cursor, open-source agents) as an engineering force multiplier—with rigorous review, testing, and validation of all AI-generated code before production
Comfort working in a hybrid environment (Mississauga office, 4 days/week)

Nice To Haves

Experience as a technical founder or early technical leader at a security scale-up
Experience with format-preserving encryption (FPE), tokenization vaults, and vaultless tokenization architectures as a consumer/integrator
Contributions to open-source in security, data platforms, or AI
Experience designing agentic AI systems in adversarial settings—tool use, multi-agent coordination, human-in-the-loop gating, prompt injection hardening
Deep experience with event-driven architectures (Kafka, NATS) at scale
Familiarity with MITRE ATLAS, NIST AI RMF, OWASP LLM/ML Top 10, and how they apply to security product architecture
Public technical presence—conference talks, published papers, standards work, or technical writing that has influenced the field
Familiarity with configuration-as-code systems (we use Groovy) and infrastructure-as-code at depth
Cross-paradigm performance analysis experience (VisualVM/JProfiler, pprof, Chrome DevTools/V8 Profiler)—you can profile and fix the hardest production performance problems yourself

Responsibilities

Own the multi-year technical roadmap and architecture vision for the DataStealth DSP across discovery, classification, tokenization, encryption, and key management
Define and evolve engineering standards, platform RFCs, technology selection, and "paved paths" that Principal and Distinguished Engineers build on
Partner with the CTO, product, and security leadership on build-vs-buy, platform bets, and competitive technical strategy
Represent DataStealth's architecture externally to enterprise customers, design partners, auditors (PCI-DSS, SOC 2), and the broader security community
Write production code in our hardest, highest-risk subsystems—tokenization engine internals, high-throughput data-path services, security-critical platform components, and cross-cutting platform libraries
Lead applied research and experimental development to de-risk our most ambitious projects: timeboxed prototypes, spikes, and reference implementations that the broader team then productionizes
Set the quality bar through exemplar code, design reviews, and technical mentorship of Principal and Distinguished Engineers
Work across the stack using the right language for the job: Java (primary), TypeScript/Node.js, Golang, and Rust
Own end-to-end security architecture for the platform: threat models, trust boundaries, applied cryptographic design, key hierarchies, HSM integration, and compliance boundaries for PCI-DSS, SOC 2, GDPR, and related frameworks
Apply the right cryptographic tools for the job—not invent them. You know which primitives to use, which libraries to trust, how to design key hierarchies and rotation, where HSM boundaries belong, and how to structure systems so compliance and operational reality both hold
Act as the final technical escalation point for novel security questions, adversarial scenarios, and high-stakes architectural trade-offs
Drive secure-by-design engineering culture: threat modeling as a first-class engineering artifact, not an afterthought
Define and lead DataStealth's application of AI and ML to security problems—data classification, anomaly and sensitivity detection, analyst augmentation, and agentic automation
Own the technical strategy for combining classical detection (regex, structured matchers, tokenization) with ML-based classification (transformer classifiers, embedding-based similarity, small distilled models) and LLM-based augmentation where appropriate
Establish DataStealth's defensive posture around AI-specific risks: prompt injection, training data leakage, model poisoning, and adversarial ML—aligned to NIST AI RMF, OWASP LLM/ML Top 10, and MITRE ATLAS
Evaluate and prototype emerging patterns (agentic security workflows, RAG over telemetry, privacy-preserving inference) and make clear recommendations on what DataStealth adopts, builds, or rejects
Set architectural direction for cloud-native deployment across AWS, Azure, and GCP—resilience, observability, cost, multi-region, and regulated-workload patterns
Define standards for CI/CD, container orchestration (Kubernetes/Docker), observability (Prometheus, Grafana, OpenTelemetry, ELK), and infrastructure-as-code (Terraform, Pulumi)
Lead architectural decisions on event-driven backbones, data stores across paradigms, and high-throughput processing systems
Provide technical leadership to the Principal and Distinguished Engineer cohort who report to you—design review, architectural direction, unblocking, and craft development through RFCs, architecture guilds, and direct technical mentorship
Work as a principal technical lead, not a traditional line manager—the executive team handles performance reviews, compensation, and the bulk of people-management load so you can stay deeply technical
Drive AI-augmented engineering practices across the team—directing agentic AI coding tools (Claude Code, Copilot, Cursor, open-source agents) as disciplined engineering partners, setting the bar on review, testing, and production quality for AI-generated code
Help hire, grow, and retain our most senior technical talent; raise the technical bar through mentorship, documentation, and visible engineering excellence
Work cross-functionally with Product, Security, Customer Success, and executive leadership to translate the hardest customer problems into coherent technical strategy