Rackspace Us Inc.
Sr Forward Deployed Engineer
US-Work from Home · Senior
Sponsorship not specifiedDetected 7 hours ago
PythonReactVue.jsNode.jsFull-Stack DevelopmentSQLNoSQLVector DatabasesCloud PlatformsDockerKubernetesCI/CDDevOpsPlatform EngineeringMachine LearningData EngineeringLLMsRAGAgentic AILangGraphAI OrchestrationCRMSupply ChainERP
About the role
- This role combines deep technical engineering with business acumen, customer empathy, and end-to-end solution ownership.
- You become the technical bridge between Rackspace's AI platform capabilities and the customer's most pressing business challenges.
- This role is ideal for someone who thrives at the intersection of engineering, strategy, and customer engagement and wants the autonomy and impact typically found at an AI startup, backed by the scale and resources of a global technology company.
Responsibilities
- Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.
- Drive rapid prototyping and POCs that demonstrate tangible business value within days to weeks.
- Serve as the primary technical owner across the full project lifecycle: scoping, architecture, build, deployment, and post-launch optimization.
- Architect production-grade Enterprise AI applications on Partner Foundry Solutions or Rackspace Private Cloud and GPU infrastructure, integrating with enterprise systems (ERP, CRM, data warehouses, data lakes).
- Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases (Pinecone, Weaviate, AstraDB), and knowledge base frameworks.
- Develop and fine-tune LLM/SLM solutions
- implement RAG architectures (LlamaIndex, Haystack) and orchestrate multi-agent workflows (LangChain, LangGraph, CrewAI).
- Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that scale future engagements.
- Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies.
Requirements
- Bachelor's degree in computer science, engineering, or related technical discipline required.
- Additional experience may substitute for the degree.
- Must be Palantir certified.
- 10+ years in software engineering, data engineering, or AI/ML delivery
- at least 4+ years in customer-facing or field roles.
- Deep full-stack proficiency: Python (required), Node.js/Go, React/Vue, SQL/NoSQL databases.
Skills
- Experience integrating across heterogeneous enterprise systems
- ERP, data warehouses, data lakes, streaming architectures.
- Ability to translate ambiguous customer needs into actionable engineering plans under tight timelines.
- Excellent communication skills - comfortable with C-suite presentations, technical workshops, and cross-functional collaboration.
- Experience with Palantir Foundry, AIP, ontology modeling, Uniphore BAIC, or similar Enterprise AI development platforms.
- Knowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.
- Docker, Kubernetes, CI/CD, GPU infrastructure, cloud-native deployment patterns.
- Experience integrating across heterogeneous enterprise systems - ERP, data warehouses, data lakes, streaming architectures.
- Familiarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware).
- Prior experience in technology consulting, AI startups, or Forward Deployed / Solutions Engineering roles.
- Domain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing.
- Experience with knowledge graphs, semantic modeling, and ontology-driven data management.
Compensation
- Our compensation reflects the cost of labor across several geographic markets.
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