<p>The AI/ML Solutions Architect will lead the design, development, and deployment of advanced AI/ML solutions. This role combines deep technical expertise with strategic thinking to ensure AI/ML initiatives are successfully integrated into business operations. You will work closely with data scientists, engineers, and stakeholders to create architectures that maximize performance, scalability, and reliability.</p><p> </p><p><strong>Key Responsibilities:</strong></p><ul><li>Design end-to-end AI/ML architectures, including data pipelines, model training, deployment, and monitoring.</li><li>Collaborate with stakeholders to define AI/ML solution requirements aligned with business objectives.</li><li>Provide technical leadership and guidance to teams implementing AI/ML models and systems.</li><li>Develop scalable and secure solutions using cloud platforms (AWS, Azure, GCP) and MLOps best practices.</li><li>Ensure seamless integration of AI/ML models into existing IT systems and workflows.</li><li>Conduct feasibility studies, prototyping, and performance evaluations for new technologies and frameworks.</li><li>Stay updated on advancements in AI/ML and recommend innovative solutions to meet emerging needs.</li><li>Document technical designs, workflows, and implementation plans to ensure clarity and reproducibil</li></ul><p><br></p>
<p>Overview</p><p>We are seeking an AI / Machine Learning Engineer to design, build, deploy, and govern scalable ML and AI solutions across the enterprise. This role combines hands‑on model development with strong ownership of AI governance, risk management, and responsible AI practices to ensure models are explainable, secure, compliant, and production‑ready.</p><p>eKey Responsibilities</p><ul><li>Design, develop, train, and deploy machine learning and AI models for structured and unstructured data use cases</li><li>Build end‑to‑end ML pipelines including data ingestion, feature engineering, training, evaluation, deployment, and monitoring</li><li>Implement MLOps practices for versioning, CI/CD, model lifecycle management, and automated retraining</li><li>Collaborate with data engineers, product managers, and business stakeholders to translate requirements into AI solutions</li><li>Monitor model performance, drift, bias, and data quality in production environments</li><li>Optimize model accuracy, scalability, latency, and cost efficiency</li><li>Develop reusable ML components, libraries, and frameworks to accelerate delivery</li></ul><p>AI Governance & Risk Responsibilities</p><ul><li>Embed AI governance controls across the model lifecycle (design, development, testing, deployment, decommissioning)</li><li>Ensure models meet enterprise standards for explainability, transparency, fairness, and auditability</li><li>Implement model documentation, lineage, and traceability (data sources, features, assumptions, limitations)</li><li>Perform model validation activities including bias testing, robustness testing, and performance benchmarking</li><li>Support regulatory, compliance, and legal requirements (e.g., model risk management, data privacy, internal audits)</li><li>Partner with security teams to ensure secure model development and protection of sensitive data</li><li>Contribute to responsible AI policies, standards, and best practices across the organization</li></ul>
<p>Overview</p><p>We are seeking an AI / Machine Learning Engineer to design, build, deploy, and govern scalable ML and AI solutions across the enterprise. This role combines hands‑on model development with strong ownership of AI governance, risk management, and responsible AI practices to ensure models are explainable, secure, compliant, and production‑ready.</p><p><br></p><p>Key Responsibilities</p><ul><li>Design, develop, train, and deploy machine learning and AI models for structured and unstructured data use cases</li><li>Build end‑to‑end ML pipelines including data ingestion, feature engineering, training, evaluation, deployment, and monitoring</li><li>Implement MLOps practices for versioning, CI/CD, model lifecycle management, and automated retraining</li><li>Collaborate with data engineers, product managers, and business stakeholders to translate requirements into AI solutions</li><li>Monitor model performance, drift, bias, and data quality in production environments</li><li>Optimize model accuracy, scalability, latency, and cost efficiency</li><li>Develop reusable ML components, libraries, and frameworks to accelerate delivery</li></ul><p>AI Governance & Risk Responsibilities</p><ul><li>Embed AI governance controls across the model lifecycle (design, development, testing, deployment, decommissioning)</li><li>Ensure models meet enterprise standards for explainability, transparency, fairness, and auditability</li><li>Implement model documentation, lineage, and traceability (data sources, features, assumptions, limitations)</li><li>Perform model validation activities including bias testing, robustness testing, and performance benchmarking</li><li>Support regulatory, compliance, and legal requirements (e.g., model risk management, data privacy, internal audits)</li><li>Partner with security teams to ensure secure model development and protection of sensitive data</li><li>Contribute to responsible AI policies, standards, and best practices across the organization</li></ul>
<p><strong>Azure Developer</strong></p><p>We are seeking a knowledgeable <strong>Azure Developer</strong> to build cloud-native applications and services using Microsoft Azure technologies. This role is ideal for someone who enjoys designing scalable solutions, working with modern cloud tools, and collaborating closely with software and cloud engineering teams. The ideal candidate will have strong development skills, deep understanding of Azure services, and a passion for cloud innovation.</p><p><strong>Responsibilities</strong></p><ul><li>Develop cloud-based applications using Azure Functions, App Services, Logic Apps, and related services</li><li>Build APIs, microservices, and serverless workloads using .NET, C#, or other Azure-supported languages</li><li>Implement Azure integrations using Service Bus, Event Hub, API Management, or Durable Functions</li><li>Create and optimize Azure DevOps pipelines for CI/CD automation</li><li>Develop Infrastructure-as-Code templates using ARM, Bicep, or Terraform</li><li>Collaborate with architects and DevOps teams to ensure scalable cloud designs</li><li>Troubleshoot application issues, performance bottlenecks, and integration problems</li><li>Monitor cloud workloads, logs, costs, and performance metrics</li><li>Maintain documentation for Azure solutions, APIs, and deployment procedures</li><li>Participate in code reviews, design sessions, and architectural discussions</li></ul><p><br></p>
<p>Join our team as a Software Engineer Lead and play a pivotal role in modernizing our intranet application, moving from legacy systems to the latest 2025 Microsoft Server environment. You’ll lead the conversion effort for web-hosted business applications using C# and .NET technologies, directly supporting a critical ERP upgrade. This is a high-impact opportunity to ensure system stability, technical excellence, and to shape future IT capabilities at a leading organization.</p><p><strong>Key Responsibilities:</strong></p><ul><li>Lead and execute the migration of the intranet application from legacy .NET/Server 2020 to .NET/Server 2025, ensuring performance and reliability.</li><li>Collaborate with stakeholders and technical teams to scope, design, and deliver the application conversion and ERP code base upgrade.</li><li>Develop scalable and maintainable C# .NET solutions, adhering to industry best practices for code modernization, testing, and deployment.</li><li>Manage hosted server environments, optimize application performance, and ensure robust integration with ERP systems.</li><li>Build and oversee DevOps pipelines for CI/CD and automated testing to ensure seamless upgrades and ongoing system health.</li><li>Mentor software team members, foster collaboration, and help drive ongoing digital transformation and technical upskilling.</li></ul><p><br></p>
<p><strong>DevOps Engineer</strong></p><p>We are seeking a motivated <strong>DevOps Engineer</strong> to enhance automation, streamline deployments, and support modern cloud-native infrastructure. This role is ideal for someone who enjoys improving system reliability, optimizing pipelines, and enabling faster development workflows.</p><p><strong>Responsibilities</strong></p><ul><li>Build, maintain, and optimize CI/CD pipelines using tools like Azure DevOps, GitHub Actions, or Jenkins</li><li>Support containerized environments using Docker and Kubernetes</li><li>Manage infrastructure automation using Terraform, Helm, Ansible, or Bicep</li><li>Monitor application performance, system uptime, and deployment health</li><li>Troubleshoot build failures, pipeline issues, infrastructure drift, and deployment errors</li><li>Manage configuration management across multiple environments</li><li>Collaborate with developers and cloud engineers during releases and application migrations</li><li>Implement logging, monitoring, and alerting solutions</li><li>Maintain documentation for deployments, pipelines, and CI/CD procedures</li></ul><p><br></p>
<p>As a Senior Software Developer, you will play a critical role in designing, developing, and maintaining robust software solutions. You will collaborate with cross-functional teams, mentor junior developers, and contribute to the technical direction of projects. Your expertise will ensure the delivery of scalable, secure, and maintainable systems that align with business objectives.</p><p> </p><p><strong>Key Responsibilities:</strong></p><ul><li>Lead the design and development of software applications, ensuring adherence to best practices and coding standards.</li><li>Collaborate with product managers, architects, and stakeholders to gather requirements and define technical specifications.</li><li>Develop scalable and maintainable code using modern programming languages and frameworks.</li><li>Conduct code reviews, provide constructive feedback, and mentor junior team members.</li><li>Troubleshoot and resolve complex software issues, ensuring minimal downtime and impact.</li><li>Optimize application performance, scalability, and security through continuous improvement.</li><li>Contribute to the design and implementation of APIs, microservices, and distributed systems.</li><li>Stay updated on emerging technologies and recommend innovative solutions to enhance development practices.</li><li>Participate in Agile ceremonies, including sprint planning, daily stand-ups, and retrospectives.</li><li>Ensure proper documentation of code, processes, and technical decisions.</li></ul><p><br></p>