Role Description CTG is seeking to fill a Senior Azure AI / MLOps Engineer position for our client. - Design and implement enterprise-scale Azure AI/ML platforms supporting production workloads. - Build and operationalize end-to-end MLOps pipelines using Azure ML, Microsoft Fabric, and CI/CD frameworks. - Architect secure, scalable Azure environments (VNets, RBAC, Entra ID, private endpoints, Key Vault). - Develop and deploy ML models with full lifecycle automation (training, validation, registration, monitoring, rollback). - Build Microsoft Fabric Lakehouse architectures using medallion design (Bronze/Silver/Gold). - Develop data ingestion pipelines integrating SAP, Snowflake, Azure SQL, IoT, and manufacturing systems. - Implement monitoring, observability, and alerting using Azure Monitor, Log Analytics, and Application Insights. - Design dashboards and operational reporting using Power BI and Azure Workbooks. - Enable real-time and near-real-time analytics using Microsoft Fabric Eventstreams and KQL databases. - Ensure security, compliance, governance, and cost optimization across AI/ML environments. Qualifications - Azure (Machine Learning, Fabric, Data Factory, Monitor, Key Vault, Networking) - Strong MLOps expertise (CI/CD, MLflow, model lifecycle management) - Python, PySpark, and data engineering pipelines - Infrastructure as Code (Terraform, Bicep, or ARM) - Cloud security, identity management, and enterprise architecture - Power BI (semantic models, dashboards) - Lakehouse architecture (medallion pattern) - Strong understanding of DevOps and production ML systems - Experience with real-time data processing (KQL, Eventstreams) preferred Requirements - 5+ years in cloud engineering, MLOps, data engineering, or AI platform roles - Proven experience building production-grade ML pipelines in Azure - Experience with enterprise data integrations (SAP, Snowflake, Azure SQL, IoT systems) - Experience implementing cloud governance, security, and monitoring frameworks - Background in manufacturing, supply chain, or industrial analytics preferred - Experience working in enterprise or Agile cross-functional teams Education - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field - Microsoft Azure certifications strongly preferred: - Azure Solutions Architect Expert - Azure AI Engineer Associate - Azure Data Engineer Associate - Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. To Apply To be considered, please apply directly to this requisition using the link provided. Kindly forward this to any other interested parties. Thank you! The expected base salary for this position ranges from $89.00 to $94.00/hour. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. In addition to salary, a competitive benefit package is also offered.

Role Description As a Founding Applied AI Engineer at Valent, you will help design and build the core intelligence layer of the product. This role is focused on applying modern AI techniques to messy enterprise problems involving documents, retrieval, reasoning, workflow automation, and human-in-the-loop review. - Help build systems that extract structured information from supplier documents, specifications, certificates, declarations, questionnaires, audit evidence, and regulatory files. - Power AI-assisted workflows for document collection, evidence packet assembly, customer requests, and audit preparation. - Use retrieval, ranking, and document understanding to help users find the right evidence across fragmented sources. - Generate draft responses, summaries, checklists, and compliance artifacts that remain reviewable and auditable by humans. - Build evaluation pipelines to measure quality, reduce hallucination, and improve reliability over time. - Design AI workflows that know when to act autonomously and when to escalate to a human. - Integrate AI features into a polished enterprise product experience. Qualifications - Strong software engineering fundamentals and experience shipping production systems. - Hands-on experience building with LLMs, retrieval systems, document AI, agents, or applied machine learning systems. - Ability to take AI systems from prototype to production. - Comfortable working across the stack when needed. - Ability to write clean, maintainable code and make sound technical tradeoffs. - Care about reliability, observability, testing, and product quality. - Ability to reason from first principles about when AI should automate, assist, or stay out of the way. - Interest in solving messy operational problems, not just building polished demos. - Clear communication in writing and comfort working remotely. - Ability to overlap for part of the day with U.S. Eastern Time. - Desire to join early and help shape the foundation of a company. Requirements - Experience with LLM application development. - Familiarity with RAG systems and vector databases. - Experience in document parsing, OCR, extraction, or classification. - Knowledge of evaluation frameworks for AI systems. - Experience in workflow automation or agentic systems. - Background in enterprise SaaS. - Familiarity with compliance, supply chain, manufacturing, regulatory, or quality workflows. - Experience with React, TypeScript, Node.js, Python, Postgres, or cloud infrastructure. Benefits - Work remotely from India on a U.S.-based enterprise AI product. - Build AI into workflows where the value is operational, measurable, and immediate. - Join early enough to have meaningful influence over architecture, product, and culture. - Work on hard problems at the intersection of AI, enterprise workflow, compliance, and manufacturing. - Help define what modern compliance operations software should look like.

• Build AI Agents with domain context for specialized tasks, including multi-step reasoning, tool use, and autonomous decision-making • Design and implement agentic workflows — orchestrating LLMs, retrieval systems, and external tools into reliable, production-grade pipelines • Integrate agents with client applications, APIs, and enterprise systems • Evaluate, iterate on, and optimize agent performance using structured testing, tracing, and observability • Deploy and maintain generative AI solutions in production environments (APIs, microservices, cloud architecture) • Document your work, follow best practices for LLMOps, and help shape AI development standards at Appsilon • Work closely with Data Engineers, Developers, and Analysts to integrate GenAI solutions into full-scale applications

Role Description We’re seeking a Senior AI Engineer to join our Professional Services team to design, build, and operationalise AI solutions that deliver measurable value for enterprise clients, working across the AI lifecycle from prototyping to production. Must be based anywhere in Australia, a citizen, and ideally hold security clearance. - Solution Design & Delivery: Work with clients to understand requirements, shape technical solutions, and deliver Agentic AI and GenAI workloads on Azure. Build production‑grade applications with CI/CD, monitoring, and observability. - GenAI & RAG Engineering: Develop robust RAG pipelines, optimise prompts, improve latency/cost, and design evaluation/test frameworks for LLM‑based systems. - MLOps & Platform Engineering: Implement MLOps with Azure ML/Databricks including experiment tracking, model registry, feature stores, automated deployment, and IaC. Establish operational telemetry and model monitoring (drift, bias, quality). - Data & Integration: Work with data engineers across ADLS, Delta Lake, EventHub, Synapse/Fabric, APIs, and vector databases to enable scalable hybrid retrieval architectures. - Security, Governance & Consulting: Apply enterprise‑grade security (Entra, networking, secrets, RBAC), embed responsible AI practices, and produce HLD/LLDs. Lead workshops, present to stakeholders, mentor engineers, and contribute to reusable components and accelerators. Qualifications - 7–10+ years in software/data/AI engineering, including 1 year in Agentic AI. - Experience delivering enterprise Search/RAG/virtual agent solutions on Azure. - Strong hands‑on skills with Azure, Databricks, and Azure ML. - Proven technical leadership, mentoring, and cross‑team collaboration. - Preferably: code/design artefacts, Azure/Databricks certifications, or related academic background. Requirements - Tools & Platforms: Python, Microsoft Foundry, LangChain/Semantic Kernel, Azure AI Search/Redis/pgvector, ADLS, Delta Lake, Databricks, Synapse/Fabric, GitHub Actions/Azure DevOps, Docker, AKS, Key Vault, Bicep/Terraform, Azure Monitor, Prometheus/Grafana. Benefits - Be part of a team that leverages modern technologies to solve real problems and provides top level of customer satisfaction. - Work with a Microsoft Partner of the Year award winner with multiple specialisations. - Be supported by experienced peers and leaders that value technical expertise and encourage innovation, with clear career pathways and ongoing learning. - Enjoy a supportive workplace that promotes inclusion, flexibility, diversity, and celebrates differences. - Take advantage of largely working from home in our remote/hybrid workplace and enjoy the flexibility to balance your life. - Thrive in a community with strong values: #BeTrue #TeamUp #StandOut #ThinkAhead #FearLessAchieveMore.