Translate approved AI architectures into secure, scalable, and maintainable production-ready systems using LangChain and LangGraph. Build and deploy LLM-powered applications, agentic workflows, and RAG solutions while ensuring operational readiness and performance.
The engineer will translate agentic AI architectures into secure, scalable production deployments using LangChain and LangGraph. They will also embed with customer teams to implement RAG, observability, and evaluation pipelines while ensuring operational readiness.
The UX Designer will conduct user research and usability testing to create intuitive, user-centered digital experiences. They will collaborate with product and engineering teams to translate requirements into wireframes, prototypes, and high-fidelity designs.
The engineer will design, implement, and maintain the SCCM/MECM infrastructure while managing software packaging and enterprise-wide deployments. They are also responsible for performing OS imaging, patch management, and providing Tier 2/3 support for SCCM-related incidents.
Design, develop, and maintain automated test suites for REST APIs and perform advanced SQL-based database validation. Collaborate with cross-functional teams to integrate tests into CI/CD pipelines and ensure system reliability across distributed services.
Lead end-to-end delivery of technology projects by coordinating cross-functional teams including Engineering, Product, and QA. Manage project scope, timelines, budgets, and risks while ensuring alignment with business objectives and healthcare industry standards.
The Principal Engineer will lead architectural decisions for legacy-to-modern platform transitions and provide mentorship to scrum teams. They are responsible for developing front-end and back-end functionality while ensuring the platform meets high standards for quality, scalability, and performance.
Define and lead the AI validation strategy for LLMs, RAG systems, and agent-based workflows. Build automated evaluation pipelines and implement AI guardrails to ensure production-ready, safe, and reliable AI solutions.
Design, build, and deploy scalable backend services and data pipelines using Python and Java on Google Cloud Platform. Integrate AI/LLM capabilities into applications while maintaining high security and code quality standards.
You will play a key role in designing, developing, and maintaining robust backend systems that power the company's AI-driven applications. You will collaborate with the engineering team to ensure high-quality code and scalable architecture.
Drive new business generation within enterprise-level retail and logistics companies. Build and manage a high-value sales pipeline through strategic prospecting and executive networking to meet senior-level quotas.
Design and deploy scalable APIs and production-ready agentic solutions using Go. Collaborate with stakeholders and cross-functional teams to translate business needs into technical requirements and high-quality API integrations.
Lead the validation and quality strategy for AI-powered systems, including LLMs, RAG applications, and agent-based workflows. Build automated evaluation pipelines and implement AI guardrails to ensure production-ready, safe, and accurate AI solutions.
Design and maintain scalable backend services using Node.js and event-driven architectures. Integrate cutting-edge AI capabilities, including LLMs and RAG, into modern cloud applications.
Lead and develop a team of principal-level engineers while managing delivery visibility and dependencies for a large-scale modernization program. Act as a coordination layer between engineering teams and senior leadership to ensure alignment with program standards and remove organizational friction.
Design and implement scalable APIs and production-ready agentic solutions using Go. Collaborate with stakeholders and cross-functional teams to translate business needs into technical requirements and high-quality backend architectures.
Design, develop, and deploy scalable backend services and microservices using Java, Python, and GCP. Build reliable data pipelines and support the integration of Large Language Models and AI-powered services.
Lead the design and development of scalable cloud-native backend solutions and secure microservices using Java, Python, and GCP. Provide technical leadership by mentoring engineers, conducting design reviews, and managing the application security posture.
Design and deploy scalable backend services, APIs, and data pipelines using Java, Python, and GCP. Support the integration of Large Language Models and AI-powered services while maintaining high code quality and security.
