Lead the technical migration from legacy Salesforce environments to ServiceNow while managing a comprehensive inventory of reporting assets. Collaborate with U.S. client leadership to ensure business continuity and data integrity throughout the 9-month transition project.
Develop and deploy production-grade machine learning models and NLP techniques to extract insights from complex supply chain data. Collaborate with engineering teams to build scalable data pipelines and translate analytical findings into actionable business strategies.
Maintain and modernize legacy Delphi applications while developing new features using modern web architectures. Build and automate business processes using Zoho platforms and engineer scalable full-stack services with Python or C#.
Architect and maintain robust end-to-end web applications using Python and JavaScript while leading legacy system modernization initiatives. You will also leverage AI tools to accelerate development and provide technical mentorship to peer developers.
The Operations Engineer will investigate and resolve data incidents while overseeing complex ETL/ELT pipelines and data warehouse structures. They will also maintain BI dashboards and automate operational workflows using Python or PowerShell to ensure data integrity.
Design, architect, and maintain scalable ETL/ELT data pipelines while orchestrating complex data workflows using tools like Airflow and Azure Data Factory. Collaborate with cross-functional teams to support AI products, RAG systems, and optimize database performance for high-volume transactional data.
Design semantic models, curated analytical views, and resilient ETL/ELT pipelines for analytical and AI use cases. Optimize database performance and implement data governance, security, quality, monitoring, and anonymization practices while collaborating with AI engineering teams.
Lead the development of robust .NET architectures and manage SQL database environments to ensure high performance and scalability. Mentor junior and mid-level engineers while driving technical excellence and managing technical debt.
The AI Product Owner will lead cross-functional teams to develop and scale AI-powered solutions, including LLM applications and RAG implementations. They are responsible for defining product strategy, managing the backlog, and ensuring compliance and quality standards are met for enterprise clients.
You will manage and provision end-to-end Azure infrastructure using Infrastructure as Code while maintaining robust CI/CD pipelines. Additionally, you will collaborate with cross-functional teams to secure data layers and deploy containerized AI and backend services.
You will design, develop, and modernize high-performance enterprise applications using the Microsoft stack, specifically C# and Blazor. You will also lead tech stack upgrades, optimize application performance, and collaborate with cross-functional teams to deliver production-ready features.
The developer will lead application modernization initiatives, including code analysis, architectural refactoring, and tech stack upgrades within agile Scrum PODs. They are responsible for designing scalable web applications and establishing engineering best practices using the latest Microsoft technologies.
You will architect and optimize an agent-ready data foundation, including semantic models and high-performance analytical views. Additionally, you will lead the implementation of data governance frameworks and collaborate with AI teams to align data structures with RAG and Agentic AI workflows.
You will architect and deploy a hierarchical multi-agent platform using LangGraph to transition legacy workflows into autonomous systems. Additionally, you will implement observability, automated evaluation harnesses, and security guardrails to ensure high-performing AI agent reliability.
You will own the reliability, scalability, and automation of cloud-native infrastructures while acting as the primary architect for CI/CD pipelines. Additionally, you will implement robust monitoring, security best practices, and mentor engineering teams on DevOps methodologies.
Design, build, and deploy production-ready AI agents and agentic workflows using frameworks like LangGraph and CrewAI. Orchestrate autonomous systems by connecting AI capabilities to enterprise data sources and tools via RAG and Model Context Protocol.
You will architect and develop enterprise-grade backend services and web APIs while optimizing complex data layers and ORM integrations. Additionally, you will lead technical research and collaborate within an Agile Scrum POD to deliver high-performance, maintainable .NET solutions.
The Senior Data Engineer will design and maintain scalable data pipelines and architectures to ensure reliable data ingestion and transformation. They will also collaborate with stakeholders to define data models and mentor junior team members.
You will architect and deploy autonomous agentic workflows and multi-agent systems using cutting-edge LLM frameworks and cloud infrastructure. Additionally, you will lead technical execution, establish observability and security guardrails, and mentor engineering teams throughout the AI development lifecycle.
You will own the technical health and architectural evolution of mission-critical web application frontends. Responsibilities include leading React development, optimizing performance, and mentoring junior engineering team members.
Design and implement scalable backend systems and APIs to support e-commerce logistics and real-time inventory synchronization. Collaborate with stakeholders and the CTO to align technical execution with business strategies while mentoring team members.
Own the quality assurance strategy and execute manual testing across web, mobile, and API layers for mission-critical applications. Collaborate with automation engineers to identify test cases for script transition and mentor junior QA staff.
The Senior Engineer will own the technical health and architectural evolution of critical Java backends, acting as the anchor for complex 3-tier architectures and SQL databases. Key duties include leading robust Java development, designing RESTful integrations, managing SQL environments, and elevating team output through mentorship and code reviews.
The Senior QA Automation Engineer will own the quality strategy and automated testing framework for mission-critical applications, focusing on building scalable test suites across API, Web, and Mobile layers. This role involves driving a quality-first culture, identifying edge cases, reducing manual testing overhead, and mentoring other engineers on modern testing methodologies.
The MLOps Engineer will design, deploy, and maintain scalable and ethical autonomous AI systems. Key tasks include model deployment, cloud infrastructure management, automation of workflows, and ensuring compliance with security and ethical standards.
Lead the architectural design of complex agentic AI solutions and provide technical guidance to junior developers. Design and develop advanced agentic AI systems while ensuring adherence to ethical guidelines and regulatory standards.
