Job Role:Staff/ Principal Software Engineer
Location: Hybrid job at St Louis, MO(3 Days Onsite must)
Duration : 6-12+ Months Contract
Role SummaryPosition: 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| Category | Technologies |
|---|
| Backend | Java, Spring Boot, REST APIs, Microservices |
| Architecture | Distributed Systems, Event-Driven Architecture |
| Cloud | AWS |
| Edge/CDN | Edge Workers, CDN Functions, Lambda@Edge |
| Languages | Java, JavaScript/TypeScript, Python |
| AI/ML | ML Inference, Feature Pipelines, Model Serving, Model Registry |
| AI/Data Platform | Databricks or equivalent |
| Security/Identity | JWT, JWS, PKI, OAuth 2.0, Token Verification |
| Dev Tools | GitHub Copilot, LLM-powered workflows, Agentic Coding Assistants |
| Observability | Distributed 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.