Jobs at TechBiz Global

Lead end-to-end training, fine-tuning, and optimisation of LLMs and SLMs on GPU infrastructure. Build and manage ML training pipelines, prepare and process large real-world datasets, select models and frameworks, apply efficient fine-tuning methods, monitor performance, troubleshoot GPU and data-pipeline issues, and collaborate to deploy models to production.

Develop, configure, and maintain AVEVA System Platform (InTouch, Application Server, Historian) HMI applications; integrate I/O servers and OPC drivers; troubleshoot and optimize systems; perform updates, backups, and migrations; support commissioning and provide second-level support and on-call duties.

Manage a portfolio of online advertising clients, build relationships to ensure retention, monitor and optimize campaign performance, produce and interpret reports, provide client support via chat/email/tickets, coordinate with internal teams, and research market trends to recommend strategies for improved campaign results.

Serve as primary client contact to gather and document payments-related requirements, coordinate configuration, testing/UAT, releases, and provide post-go-live production support. Manage incidents, SLAs, escalations, reporting, and root cause analysis while working with Delivery, Technical, QA teams and participating in a 24/7 support roster and varied shift schedules.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Lead end-to-end development and integration of AI features (LLMs/ML) into web/mobile apps and APIs. Design AI-first UX, craft and optimize system prompts, build agentic workflows (LangChain/CrewAI/AutoGen), implement error-handling and hybrid cloud/on-prem deployments, and collaborate within product squads using Agile/Scrum.

Design and implement CI/CD and IaC for LLMs, automate model and dataset versioning, provision GPU/TPU infrastructure, enable safe experiment gates and progressive delivery, and build monitoring/observability and feedback loops for production LLM endpoints.

Lead product design and strategy for a new AI-powered cyber risk platform. Define information architecture, user journeys, wireframes, and MVP scope; run discovery, validation, and usability testing; manage backlog and ship features with engineering, security, and data teams. Represent product to customers, partners, and investors as a founding team member.

Lead and grow a small engineering team as a hands-on founding engineering lead, designing and building core backend, identity, and security platform components. Own architecture, delivery, CI/CD, observability, and production reliability while contributing code (~70% in Go), mentoring engineers, troubleshooting incidents, and partnering with leadership on technical strategy and hiring.

Serve as the founder's primary operations associate and executive assistant to the CEO. Own daily operations across HR, finance, admin, and internal processes; lead company projects (pricing model, country expansion); manage investor/board communication and CEO admin (calendar, travel, meetings); support hiring, onboarding, invoicing, expense tracking, PR, social media, sales materials, and ensure compliance and operational hygiene.

Lead design, build, and operate a multi-tenant AI platform and LLMOps infrastructure across cloud and on-prem. Own vector DBs, feature stores, model hosting (Kubernetes + GPU orchestration), and developer self-service tooling. Standardize LLM-as-a-service offerings and enable squads with APIs, templates, and documentation.