Jobs at Zinkworks

Analyze complex enterprise source systems, profile and validate datasets, reverse engineer undocumented data structures, and design conceptual, logical, physical, graph, and relational target models. Define source-to-target mappings, document entities and relationships, evaluate performance and scalability, and collaborate with stakeholders, architects, and engineers to implement accurate, governed data solutions.

Manage end-to-end recruitment, including sourcing, screening, interview coordination, onboarding, job posting, talent pipeline development, and candidate tracking. Partner with hiring managers, maintain recruitment data, support administrative processes, and represent Zinkworks at recruitment events and networking opportunities. The role requires strong organization, communication, adaptability, and familiarity with recruitment tools and Microsoft Office.

Executive leader responsible for Zinkworks’ product strategy, commercialisation, technology direction, product revenue, and ARR. The role requires building scalable B2B software products, achieving product-market fit, developing telecom-sector go-to-market strategies, securing enterprise customers, establishing pricing and recurring-revenue models, and leading product and technology teams. The executive will also oversee technology strategy, cloud-native and secure product development, customer acquisition, retention, expansion, and long-term product economics.

Owns the development and productionization of AI/ML models for detecting service outages, degradation, and business impact. Responsibilities include anomaly detection, time-series modeling, feature engineering, real-time model serving, monitoring, drift detection, retraining, champion/challenger evaluation, and MLOps automation. Later work includes building an LLM agent with retrieval, tool use, guardrails, evaluation, and red-teaming. Collaborates with data and backend engineers to integrate model outputs into remediation workflows.

Build backend services for an AI-driven incident management and remediation platform. Responsibilities include impact scoring, API integrations, workflow state machines, safe batch remediation, audit trails, customer communications, recovery verification, and autonomous-operation safeguards. The role requires production Python backend development, cloud deployment, CI/CD, testing, reliability engineering, and collaboration across data, ML, frontend, UX, QA, and platform teams.

Leads a data engineering squad and owns the platform’s data foundations. Designs ingestion pipelines, canonical data models, validation, quality monitoring, curated data marts, and ML feature pipelines. Scales batch and near-real-time processing for telemetry and business data while partnering on Google Cloud infrastructure, infrastructure as code, CI/CD, observability, and cost controls. Guides technical decisions, reviews code, mentors engineers, and communicates with client stakeholders.

The Scrum Master coaches agile teams toward self-management, improved flow, predictable delivery, and higher quality. Responsibilities include facilitating effective Scrum events, improving backlog quality and Definition of Done, reducing handoffs, removing systemic impediments, coaching Product Owners, and partnering with clients and leadership. Success is measured through stronger Sprint Goal achievement, reduced carryover and WIP, fewer late defects, and increased delivery predictability.

Lead presales technical engagements for telecom customers, designing cloud-native OSS/NMS and AI/ML-driven automation. Run discovery workshops, own technical POCs, craft RFP/RFI responses, translate customer needs into defensible solutions, and present to executive and technical stakeholders while partnering with delivery and engineering teams.

Lead the architecture of an enterprise Agentic AI platform on GCP for a major telecommunications provider. Define secure interactions among microservices, AI models, data pipelines, and telecom systems; establish Generative AI governance and RAG frameworks; create API and event-driven integration patterns; review architectural deliverables as Design Authority; and design orchestration frameworks across RAN, Core, OSS/BSS, and network automation environments.

Design and maintain automated test frameworks for microservices, APIs, and data pipelines. Perform backend API, integration and database testing, write BDD tests with Cucumber, validate SQL/stored procedures, automate Spring Boot/Batch apps on OpenShift/Kubernetes, integrate tests into CI/CD, and debug distributed systems using Unix tools and technologies like Kafka and Redis.

Build end-to-end prototypes for autonomous network products: frontend UIs, backend services, APIs, data flows, cloud infrastructure, and third-party integrations. Partner with AI engineers to integrate agent frameworks, implement real-time and asynchronous workflows, maintain GCP demo infrastructure, and define full-stack standards, observability, security, and deployment practices to evolve prototypes toward production.

Build production GenAI systems: implement RAG pipelines, orchestrate agentic workflows, integrate agents with enterprise systems, deploy on GCP (Cloud Run, Pub/Sub), and ensure security, observability, and operational readiness.

Design, develop, and maintain scalable Java backend services using Spring frameworks. Build RESTful microservices, integrate messaging (Kafka/ActiveMQ), support CI/CD pipelines, troubleshoot production issues, transform legacy systems to microservices, participate in code reviews, mentor juniors, and collaborate with cross-functional teams in an Agile environment.

Entry-level, in-office software developer apprenticeship combining FIT formal training with on-the-job projects. Learn programming (Python, Java), databases, Spring Boot backend, frontend basics, testing, GCP cloud, Docker and CI/CD, and AI-assisted tooling while participating in team ceremonies, completing exercises, and receiving mentorship.

Lead presales technical engagements for RAN automation, OSS and network management. Design cloud-native, closed-loop rApp/AI solutions, run trials and workshops, author RFP responses, and drive technical POCs with operator stakeholders through to technical close.