Agentic AI ArchitectureDesign and implement production-grade agentic systems using models such as Claude. Agent orchestration, tool calling, function calling, multi-agent architectures, planning and task decomposition, agent memory, context management, state machines and workflow engines, long-running agents, human-in-the-loop systems, autonomous execution, recovery and retry mechanisms, observability, and evaluation. You understand the difference between LLM → Agent → Workflow → Autonomous System, and when each is appropriate.
Agentic Loops & Self-OptimizationA major part of the role is building closed-loop systems: Goal → Plan → Execute → Observe → Evaluate → Learn → Re-plan → Execute. Systems that evaluate their own outputs, detect failed actions, identify root causes, adjust strategies, optimize prompts and tool selection, keep what works, roll back what does not, and improve over time. Reflection, critique, self-evaluation, feedback loops, reward signals, evaluation frameworks, automated experimentation, memory, retrieval, state management.
Claude / LLM EngineeringDeep practical experience with Claude/Anthropic APIs is highly desirable. Tool use, structured outputs, streaming, context management, prompt engineering, system prompts, long-context workflows, model routing, token optimization, latency and cost optimization, context compression, agent memory, LLM evaluation. Experience with other frontier models (OpenAI, Gemini, Llama or equivalent) is a plus.
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As a QA Team Lead you will design and build systems that embed quality into the development lifecycle rather than treating it as a final step. This is a hands-on leadership role working closely with product, design, and engineering to define quality ownership across squads while contributing directly through automation, tooling, and observability. Over time you will help establish and grow a scalable quality engineering function that supports the organisation as it scales.
ParcelDaily is seeking a Quality Assurance (QA) Intern to work closely with developers, product, customer service, and operations to test and improve the ParcelDaily platform. The role involves testing workflows, courier integrations, parcel bookings, payment transactions, tracking updates, and other features used by customers.
Lead technical engagement with clients - Represent the company as the primary technical point of contact throughout discovery calls, site assessments, and solution walkthroughs, building the credibility that moves deals forward.
Translate technical capability into commercial value - Articulate how drone dock, quadruped/humanoid robotics, and RaaS solutions address specific client operational challenges, enabling the sales team to sell with confidence and precision.
Own end-to-end solution design - Assess client requirements and architect the corresponding hardware, software, and connectivity solution, working closely with engineering to validate technical feasibility before commitment.
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As a QA Team Lead you will design and build systems that embed quality into the development lifecycle rather than treating it as a final step. This is a hands-on leadership role working closely with product, design, and engineering to define quality ownership across squads while contributing directly through automation, tooling, and observability. Over time you will help establish and grow a scalable quality engineering function that supports the organisation as it scales.
Assist in building AI-powered automation workflows for digital marketing, lead management, reporting, CRM, WhatsApp, websites, and internal operations.
Support the integration of LLM models such as OpenAI, Anthropic Claude, Gemini, or similar AI platforms into business workflows.
Assist in developing and connecting APIs, REST APIs, webhooks, JSON data flows, and backend logic.
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Advance your architecture skills by owning multi-service systems and delivering measurable improvements in latency, cost, scalability, or maintainability. Lead design reviews, produce architecture diagrams, and propose practical trade-offs that keep our industrial customers reliable.
Lead cross-functional delivery with product and QA, defining clear acceptance criteria and keeping releases predictable. Coordinate rollout plans, feature flags, release notes, and post-release checks that reduce surprises in production and keep factory operations stable.
Expand your technical footprint across backend and frontend stacks by applying Node.js, Python, or Java and both SQL and NoSQL databases to ship full features. Work with containerisation, Kubernetes-style orchestration, CI/CD pipelines, and cloud services to run services at scale.
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