Senior Financial Solutions Manager
Agilent Technologies
Principal Specialist, Solution Architect
Red Hat
full-time
Posted on:
Location Type: Remote
Location: Remote • New York • 🇺🇸 United States
Visit company websiteSalary
💰 $226,360 - $373,460 per year
Job Level
Lead
Tech Stack
AnsibleAWSAzureChefCloudGoogle Cloud PlatformKubernetesLinuxOpenShiftOpenStackPuppetUnixVMware
About the role
- Set mid-term objectives to guide strategic customer engagements.
- Lead major proofs of concept, workshops, and customer demonstrations.
- Serve as a subject matter expert within the region, advising on Red Hat solutions.
- Mentor colleagues within the discipline to enhance technical and strategic capabilities
- Drive collaboration across business units, engineering, and professional services
- Support the Sales team with recommendations for development and implementation of complex offerings and solutions to achieve sales quotas
- Meet revenue goals, in addition to deployment and service objectives while maintaining good relationships with existing and prospective customers
- Lead critical customer presentations/sessions/demos around business problems, Red Hat solutions, business value, competitive positioning and product capabilities and roadmaps
- Prepare detailed specifications of our offerings and implement customer installation plans
- Design solutions based on customer requirements and create and deliver solid business cases
- Design value-driven architectures and present the application and return on investment (ROI) of our technologies
- Deliver compelling recommendations and quality solutions that result in the closing of new sales
- Use your skills as a technical solutions expert and your understanding of industry best practices to deliver timely results to customers
- Share knowledge and findings to allow team members to learn from your successes and mistakes
- Focus on customer success activities
Requirements
- 5+ years of experience as a sales engineer, consultant, IT architect, Site Reliability Engineer, DevOps Engineer or an equivalent role within enterprise accounts
- Ability to interpret customers’ business and technical needs
- Understanding of complex enterprise solutions and architectures
- Excellent presentation, communication, and documentation skills
- Record of developing relationships at engineering, commercial, and executive levels throughout large enterprise IT organizations
- Advanced knowledge of UNIX or Linux systems, preferably in Red Hat platform offerings like Red Hat Enterprise Linux (RHEL), provisioning and patch management solutions like Red Hat Satellite, and configuration management technologies like: Red Hat Ansible Automation Platform, Puppet, Chef, or other related technologies
- Solid knowledge of hybrid cloud infrastructure and management solutions in the market like KVM, VMware vSphere, Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, or Red Hat OpenStack Platform
- Knowledge of technologies like clustering, directory services, identity management, SELinux, etc.
- Broad understanding of the application life cycle from development to operations and its respective practices (DevOps)
- Knowledge of key technologies in DevOps including security, and continuous integration (CI) and continuous delivery (CD) tooling
- Understanding of key Linux container technologies including kubernetes, and enterprise solutions like Red Hat OpenShift Container Platform
- Willingness to travel up to 40%
- Expertise in configuring and optimizing vLLM and other large language model (LLM) serving frameworks for performance on GPU-accelerated infrastructure.
- Proficient in GPU resource allocation, scheduling, and management within Kubernetes environments.
- Experience with various hardware accelerators and their integration into Kubernetes clusters for AI/ML workloads
- Proficient in Agentic Frameworks for Advanced AI Development
- Demonstrated expertise in leveraging cutting-edge agentic frameworks to design, develop, and deploy sophisticated AI applications.
- This includes hands-on experience with: LlamaIndex: Skilled in utilizing LlamaIndex for building intelligent information retrieval systems and enhancing the contextual understanding of large language models. This involves optimizing data indexing, query processing, and integrating various data sources to create highly efficient knowledge bases.
- LangChain: Proficient in using LangChain to orchestrate complex AI workflows, chain together different language models and tools, and create robust applications that can perform multi-step reasoning and interaction. This includes developing custom chains, agents, and memory management for dynamic and adaptable AI solutions
- LangSmith: Experienced with LangSmith for comprehensive debugging, testing, and monitoring of large language model applications. This involves leveraging its tracing capabilities to analyze execution flows, identify bottlenecks, and optimize performance for reliable and scalable AI systems.
- LangGraph: Adept at designing and implementing stateful, multi-turn conversational agents and complex decision-making systems using LangGraph. This includes modeling intricate interaction flows, managing agent states, and enabling sophisticated reasoning and response generation in dynamic environments.
- This comprehensive experience with agentic frameworks ensures the ability to architect and deliver innovative AI solutions that are robust, scalable, and capable of addressing complex real-world challenges.
- Create Services on Kubernetes for Model-as-a-Service (MaaS) and GPU-as-a-Service (GaaS)
- Model-as-a-Service (MaaS): Design and implement Kubernetes services to expose trained machine learning models as scalable, API-driven endpoints. This includes defining deployment strategies for model containers, configuring ingress for external access, and implementing service mesh solutions for traffic management, load balancing, and secure communication between model services.
- GPU-as-a-Service (GaaS): Develop and manage Kubernetes resources for providing on-demand GPU access to AI/ML workloads. This involves configuring GPU operators, device plugins, and resource quotas to ensure efficient allocation and isolation of GPU resources. Implement strategies for dynamic provisioning and de-provisioning of GPU-enabled pods to optimize cost and performance for diverse computational demands.
Benefits
- Comprehensive medical, dental, and vision coverage
- Flexible Spending Account - healthcare and dependent care
- Health Savings Account - high deductible medical plan
- Retirement 401(k) with employer match
- Paid time off and holidays
- Paid parental leave plans for all new parents
- Leave benefits including disability, paid family medical leave, and paid military leave
- Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
sales engineeringconsultingIT architectureSite Reliability EngineeringDevOps EngineeringUNIXLinuxRed Hat Enterprise Linux (RHEL)Red Hat Ansible Automation PlatformKubernetes
Soft skills
presentation skillscommunication skillsdocumentation skillsrelationship buildingmentoringcollaborationcustomer success focusstrategic thinkingproblem-solvingadvisory skills
