1 day ago
Base Salary
$166k - $243k/yr
Responsibilities
- Diagnose customer business challenges, map data landscapes, and co-design AI solutions during on-site engagements.
- Design and deliver agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.
- Own solution lifecycles from scoping and architecture through prototyping, build, deployment, and post-launch optimization.
- Build enterprise AI applications, scalable data pipelines, vector database integrations, and multi-agent workflows.
- Use full-stack and DevOps capabilities to deploy production systems and manage GPU infrastructure.
- Implement observability, monitoring, telemetry, versioning, and auditability for production AI agents.
- Identify expansion opportunities with sales and customer success and feed field insights to product and platform engineering teams.
- Create reusable reference architectures, accelerators, frameworks, and technical best practices.
- Mentor engineers and customer teams through knowledge transfer and internal AI capability development.
Requirements
- Palantir certification is required.
- At least 6 years of experience in software engineering, data engineering, or AI/ML delivery and at least 4 years in customer-facing or field roles.
- Proven experience building and deploying enterprise-scale AI/ML applications in production.
- Deep proficiency with Python, Node.js or Go, React or Vue, and SQL or NoSQL databases.
- Hands-on experience with LLMs, prompt engineering, vector databases, data pipelines, dashboards, RAG pipelines, and agent orchestration frameworks.
- Strong Docker, Kubernetes, CI/CD, GPU infrastructure, and cloud-native deployment experience.
- Experience integrating ERP systems, data warehouses, data lakes, and streaming architectures.
- Experience with Palantir Foundry, AIP, ontology modeling, Uniphore BAIC, or similar enterprise AI platforms.
- Knowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.
- Experience with agentic AI, multi-agent systems, tool use, and autonomous workflow orchestration.
- Familiarity with NVIDIA H100 or B200 GPUs, InfiniBand, OpenStack, and VMware.
- Prior technology consulting, AI startup, Forward Deployed, or Solutions Engineering experience is preferred.
- Domain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing is preferred.
- Experience with knowledge graphs, semantic modeling, and ontology-driven data management is preferred.
- Ability to translate ambiguous customer needs into engineering plans and communicate with executives, technical teams, and cross-functional stakeholders.
Benefits
- Remote work from home with approximately 25% travel for on-site customer engagements.
- Compensation may include annual bonuses or incentives, equity awards, and an Employee Stock Purchase Plan (ESPP).
- Rackspace provides equal employment opportunity and disability accommodations.
About Rackspace
Rackspace provides managed cloud and IT services for enterprises, including multicloud operations, cloud migration, private cloud, managed security, and application/platform management across AWS, Azure, Google Cloud, and VMware. It operates a services-led business model with consulting and ongoing management for regulated and mission‑critical workloads, including healthcare. Founded in 1998 and headquartered in San Antonio, Texas, Rackspace is majority‑owned by Apollo Global Management.