Support the response and resolution of priority and major incidents affecting the site.
Assist with device builds, rebuilds, deployment, backups, technology refreshes, and mobile device preparation.
Support local video conferencing, collaboration, and audio-visual technologies, including Microsoft Teams, Zoom, Cisco video conferencing, Office 365, OneDrive, and Box.
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Map how each department works today and rank tasks by time saved, cost and risk.
Keep a live AI roadmap and use-case register for the whole group.
Build and maintain AI agents and automations: quotation and RFQ drafting, contract review, tender and lead research, reporting, HR and payroll admin, and site-worker communication.
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Job SummaryWe are looking for a hands-on AI Engineer to design, develop, integrate, and deploy Generative AI, AI chatbot, and Agentic AI solutions. The role will focus on building practical AI applications and integrating LLM capabilities with existing applications, APIs, databases, and enterprise systems.Key ResponsibilitiesDesign and develop AI chatbots, copilots, and LLM-powered applications.Build Agentic AI solutions with reasoning, tool/function calling, multi-step task execution, and workflow automation.Implement RAG, embeddings, vector search, prompt engineering, and conversational memory.Work with commercial and open-source LLMs and select appropriate models based on business and technical requirements.Integrate AI solutions with REST APIs, databases, CRM/ERP systems, and enterprise applications.Develop AI integration services and APIs for existing systems and business workflows.Evaluate and optimize AI solutions for accuracy, reliability, latency, scalability, security, and cost.Collaborate with software engineers, architects, product teams, and business stakeholders.Keep up to date with developments in Generative AI, LLMs, Agentic AI, and AI automation.RequirementsBachelor's degree in Computer Science, AI/ML, Software Engineering, or a related field.3+ years of experience in AI/ML engineering, software engineering, or a related role.Hands-on experience developing LLM applications, AI chatbots, or Generative AI solutions.Practical experience with AI Agents, Agentic AI, tool/function calling, or AI workflow automation.Experience with open-source LLMs such as Llama, Qwen, Mistral, Gemma, or equivalent.Strong Python programming and software engineering skills.Experience with REST APIs, system integration, databases, and cloud/on-premise environments.Hands-on experience with RAG, vector databases, embeddings, and prompt engineering.Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent.Experience with LLM platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, and/or open-source models.Familiarity with Docker, Git, CI/CD, and production deployment.Preferred SkillsExperience serving open-source LLMs using vLLM, Hugging Face, Ollama, or equivalent.Experience with MCP, multi-agent systems, LLM evaluation/observability, fine-tuning, LoRA/QLoRA, or model optimization.Experience with AWS, Azure, or Google Cloud.Knowledge of AI security, data privacy, access control, and responsible AI.
Troubleshooting s Risk Mitigation: Identify and resolve technical bottlenecks during migration/deployment phases, ensuring minimal disruption to client operations.
Documentation s Handoff: Build standard operating procedures (SOPs), Project As-Builts, Low-Level Diagram(LLD), system architecture diagrams, and detailed handover documentation for ongoing support teams.
Process Optimization: Continuously refine deployment scripts, templates, and rollout checklists to improve implementation speed and consistency.
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Deep expertise in modern Java (17+) including concurrency, multithreading, reactive programming, build tools (Gradle/Maven lifecycle), and design principles (SOLID), with experience in performance tuning, JVM optimization and troubleshooting.
Proven hands-on experience with Spring Boot ecosystem (Security, WebFlux, Data/MyBatis), strong understanding of Spring internals (beans, AOP, request handling, serialization), and API design using REST and OpenAPI.
Strong experience designing and operating microservices on AWS using ECS, DynamoDB and Aurora, with solid knowledge of event-driven systems and services such as SQS, SNS, EventBus and Lambdas, combined with CI/CD and infrastructure-as-code practices.
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Proven hands-on experience with Spring Boot ecosystem (Security, WebFlux, Data/MyBatis), strong understanding of Spring internals (beans, AOP, request handling, serialization), and API design using REST and OpenAPI.
Strong experience designing and operating microservices on AWS using ECS, DynamoDB and Aurora, with solid knowledge of event-driven systems and services such as SQS, SNS, EventBus and Lambdas, combined with CI/CD and infrastructure-as-code practices.
Strong experience in modern testing approaches (e.g., RestAssured, TestContainers, WireMock, Localstack) and a solid understanding of cloud security, resilience, and operational excellence in enterprise environments.
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Troubleshooting s Risk Mitigation: Identify and resolve technical bottlenecks during migration/deployment phases, ensuring minimal disruption to client operations.
Documentation s Handoff: Build standard operating procedures (SOPs), Project As-Builts, Low-Level Diagram(LLD), system architecture diagrams, and detailed handover documentation for ongoing support teams.
Process Optimization: Continuously refine deployment scripts, templates, and rollout checklists to improve implementation speed and consistency.
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