• Development, implementation and maintenance of new features and modules for our software products based on PHP. • Support of continuous improvement of the product, our processes and our development teams. • Use of modern technologies and methods such as PHP, JavaScript, HTML, CSS, MySQL, Git, Scrum, etc. • Ensuring the quality, performance and security of our shop software and other applications. • Fixing bugs, optimizing existing code and producing clean, stable code.

Role Description As a Backend Engineer at Nebulock, you will own the core systems that form the foundation upon which Nebulock is built. You’ll co-own the data ingestion, transformation, and search layers that power threat hunting and detection engineering workflows for our customers. This role is ideal for engineers who love bringing clarity and order to messy, disparate, and large-scale datasets. - Design, build, and maintain scalable systems that ingest and process large volumes of security telemetry (TBs / day) - Own integrations across a wide range of data sources (EDR, IAM, Cloud, SaaS) - Own the transformation layer that turns disparate data into a normalized, enriched, and queryable model - Build an engine that correlates entities across disparate data sources - Develop and operate both real-time and batch processing systems - Work on core search capabilities across vast amounts of data - Collaborate with our internal detection engineers, threat hunters, and product engineers to ensure the Nebulock platform has the data it needs and that the data is structured correctly - Help drive the architecture and technical direction of Nebulock’s platform Qualifications - 4+ years of experience building backend distributed systems and working with data - Proficiency in Python, Java, Go, Rust, or similar - Experience with either AWS or GCP - Strong experience with data pipelines - Experience with event-driven systems - Strong understanding of system design, data modeling, and performance trade-offs - Experience with OLAP databases - Ability to adapt, iterate, and ship quickly - Hunger for growth and the desire to work in a low-ego environment Requirements - Experience with streaming data processing engines (i.e. Flink) - Experience building or working with search systems over large datasets - Cybersecurity experience - Startup experience Benefits - A dynamic startup environment with opportunities for rapid career growth - A collaborative culture that values innovation and creativity - Competitive salary and equity options - Comprehensive benefits package (including 401K) - Opportunities to travel for conferences, workshops, and team-building events

Role Description Under the general direction of the Director, AI Platforms and Solutions Delivery, the Full-Stack .NET Developer will help advance Cencora’s digital transformation by designing, building, and operating modern web applications and services on the Microsoft stack. This role focuses on delivering secure, scalable, cloud-native solutions using .NET and contemporary front-end frameworks, with exposure to integrating AI and GenAI capabilities into business applications. - Design, build, and maintain full-stack .NET applications using C#, ASP.NET Core, RESTful APIs, modern UI technologies (React, Angular, or Blazor), and responsive design principles. - Develop scalable backend services, integration layers, and data access patterns (SQL/ORM) optimized for performance and maintainability. - Integrate AI capabilities into applications: - Call Azure OpenAI, GPT models, and other LLM endpoints via backend APIs. - Implement prompt engineering, chain-of-thought, and advanced prompting techniques. - Build Retrieval-Augmented Generation (RAG) solutions using vector search (Azure AI Search, PostgreSQL pgvector, etc.). - Develop AI-powered features such as intelligent search, summarization, content generation, chat assistants, and workflow automation. - Create and maintain Python scripts for data processing, embedding generation, LLM evaluation, or prototyping AI solutions. - Collaborate with AI platform teams to integrate Azure AI services (Azure OpenAI, Azure AI Studio, Functions, etc.). - Implement observability, monitoring, and evaluation frameworks for AI components (latency, quality, cost, safety). - Contribute to CI/CD pipelines, Infrastructure as Code, DevOps practices, and responsible AI guidelines (bias detection, hallucination mitigation, compliance). - Participate in code reviews, architecture discussions, and incident management. Qualifications - Bachelor’s degree in Computer Science or equivalent relevant experience. - 5+ years of professional full-stack software engineering experience with strong emphasis on .NET ecosystem (C#, ASP.NET Core, Entity Framework, etc.). - Solid experience building REST APIs, modern web UIs, and cloud-native applications on Azure. - Strong plus: Hands-on experience integrating Large Language Models (LLMs), prompt engineering, or RAG patterns. - Advantageous (not mandatory): Exposure to Python for AI-related tasks (LangChain, LlamaIndex, Hugging Face, pandas, embedding models, etc.). - Experience with Azure AI services, vector databases, or semantic search is highly valued. - Knowledge of responsible AI practices and MLOps concepts is a plus. Requirements - Passion for building high-quality, maintainable software with strong attention to detail. - Self-motivated, pragmatic problem-solver who can work effectively amid evolving requirements. - Strong communication skills with the ability to work across engineering, product, and business teams. - Solid understanding of secure software development practices (authentication/authorization, secrets management, OWASP fundamentals). - Ability to research, evaluate, and apply new technologies responsibly, including AI capabilities, where they add measurable business value. - Thrives in collaborative environments, resolves conflicting approaches constructively, and contributes to a healthy engineering culture. Schedule Full time Affiliated Companies Affiliated Companies: AmerisourceBergen Services Corporation Equal Employment Opportunity Cencora is committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status or membership in any other class protected by federal, state or local law. The company’s continued success depends on the full and effective utilization of qualified individuals. Therefore, harassment is prohibited and all matters related to recruiting, training, compensation, benefits, promotions and transfers comply with equal opportunity principles and are non-discriminatory. Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment, please call 888.692.2272 or email hrsc@cencora.com. We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned.

• Own the CLOB engine's critical path. Profile matching and orderbook hot paths, map settlement-sensitive state transitions, and drive improvements to latency, throughput, and async engine flow backed by benchmarks and production-grade evidence. • Reduce lock contention without breaking correctness. Debug concurrency issues, design safer queueing and backpressure for orderbooks, and improve the system's ability to handle materially more markets and order flow with lower tail latency. • Build for observability and safety. Instrument improvements with pprof, metrics, logs, and traces. Establish rollback guarantees and narrower critical paths that make production incidents easier to detect, diagnose, and resolve. • Reason about settlement risk. Understand how on-chain transaction effects ripple into off-chain exchange state, and design systems that handle crossed books, ghost fills, stale orders, cancel inconsistencies, and settlement edge cases correctly. • Improve the runtime. Reduce GC pressure, optimize CPU and memory allocation behavior, and push Go runtime performance to meet the demands of a high-throughput exchange at scale. • Debug production incidents. Own latency, correctness, and settlement-state incidents end-to-end, and drive follow-through that leaves the system measurably better each time.