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Estimated Pay info$51 per hour
Hours Full-time, Part-time
Location Saint Louis, MO
Saint Louis, Missouri open_in_new

About this job

Job Description

Job Description

Job Role: Staff/ Principal Software Engineer
Location: Hybrid job at St Louis, MO(3 Days Onsite must)
Duration : 6-12 Months Contract

Role Summary
Position: Staff / Principal Software Engineer
We are looking for a highly experienced Staff/Principal Software Engineer who thrives in ambiguity, enjoys building systems from 0 to 1, and can move quickly from concept to production-ready solutions.
This is a hands-on Individual Contributor (IC) role with significant architectural ownership. You will design systems, write production code, and work at the intersection of edge computing, backend services, distributed systems, and AI/ML platforms. You will collaborate closely with Data Science, Product, and Partner teams to build scalable foundations for trust-signal processing and machine learning inference.
Key Responsibilities
  • Design and build end-to-end signal-processing flows, including CDN/edge detection, API ingestion, processing, sandbox storage, and downstream routing.
  • Architect and implement edge-layer solutions using edge-worker runtimes and CDN-layer compute for token detection, header manipulation, and signal capture with minimal latency impact.
  • Design and develop scalable backend services using Java and Spring Boot, including APIs, signal validation and normalization pipelines, data persistence, and service foundations.
  • Define integration patterns for third-party KYA and identity providers, including JWT validation, public-key caching, and deterministic signal ingestion.
  • Build platform capabilities supporting ML inference, including structured data-access layers, feature pipelines, model-serving integrations, and model-registry connectivity.
  • Partner closely with Data Science teams to move ML solutions from experimentation to production.
  • Make architecture and technology decisions related to storage, transport reliability, observability, security, and governance within AWS environments.
  • Design scalable microservices and event-driven architectures for reliable signal processing and downstream integrations.
  • Take ownership of system design decisions and communicate architecture effectively across engineering and cross-functional teams.
  • Work effectively in a fast-paced, startup-like environment with evolving requirements, rapid prototyping, and iterative architecture refinement.
Required Qualifications
  • 10 years of experience building and operating production-grade distributed systems.
  • Strong expertise in Java and Spring Boot.
  • Extensive experience designing REST APIs, microservices, and event-driven architectures.
  • Strong hands-on experience with AWS, including cloud compute, storage, networking, and IAM.
  • Hands-on experience with Edge/CDN technologies, such as:
    • Edge Workers
    • CDN Functions
    • Lambda@Edge
    • CloudFront or equivalent edge-compute platforms
  • Experience building or supporting ML inference pipelines, including:
    • Data normalization
    • Feature pipelines / feature stores
    • Model serving
    • Model-registry integrations
  • Demonstrated experience using AI-assisted development tools, such as:
    • GitHub Copilot
    • LLM-powered development workflows
    • Agentic coding assistants
  • Proven ability to build systems from 0 to 1 and work effectively with ambiguous or evolving requirements.
  • Strong system-design and architecture skills, with the ability to translate ambiguous product requirements into technical solutions.
  • Strong communication and collaboration skills with engineering, product, data science, and partner teams.
Preferred / Nice-to-Have Qualifications
  • Experience in identity, trust, or security domains.
  • Knowledge of:
    • JWT / JWS
    • PKI
    • OAuth 2.0
    • Token verification
    • Bot detection
  • Python experience for data engineering, automation, or scripting.
  • Experience with Databricks or similar AI/data platforms.
  • Experience implementing observability at scale, including:
    • Distributed tracing
    • Structured logging
    • Monitoring dashboards
  • Experience building multi-party integration layers, network services, or platform services.
  • Contributions to open-source projects or active participation in technical communities.
Technical Stack
CategoryTechnologiesBackendJava, Spring Boot, REST APIs, MicroservicesArchitectureDistributed Systems, Event-Driven ArchitectureCloudAWSEdge/CDNEdge Workers, CDN Functions, Lambda@EdgeLanguagesJava, JavaScript/TypeScript, PythonAI/MLML Inference, Feature Pipelines, Model Serving, Model RegistryAI/Data PlatformDatabricks or equivalentSecurity/IdentityJWT, JWS, PKI, OAuth 2.0, Token VerificationDev ToolsGitHub Copilot, LLM-powered workflows, Agentic Coding AssistantsObservabilityDistributed Tracing, Structured Logging, Dashboards
The source JD identifies Java Spring Boot, AWS, Edge/CDN, Python, Databricks/ML model registry, and GitHub Copilot/AI-assisted workflows as the core technology stack.
What Success Looks Like
We are looking for engineers who:
  • Build AI-enabled platforms, rather than simply consuming AI services.
  • Have shipped systems that serve ML models or feed ML inference pipelines.
  • Use AI tools and LLMs to significantly improve their engineering productivity.
  • Are comfortable operating without perfect specifications and can prototype, ship, learn, and iterate quickly.
  • Collaborate effectively with Data Science, Product, Engineering, and Partner teams.
  • Influence technical direction through code, architecture, and system design, rather than relying solely on organizational title.

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