Embedded with strategic enterprise customers to design, prototype, and deploy production-grade AI solutions (RAG, agents, knowledge graphs). Own full lifecycle, build data pipelines, manage GPU/private cloud infrastructure, integrate with enterprise systems, and mentor teams while driving product feedback and reusable IP.
About the Role: Location: Remote (US) /Travel up to 25% | Reports To: VP, Data & AI | Job Level: Senior / Principal (IC)
As a Sr. Forward Deployed Engineer (Sr. FDE) at Rackspace Technology, you will be embedded directly with our most strategic enterprise customers to architect, build, and deploy high-impact AI solutions. 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. You will own the full solution lifecycle from problem discovery and rapid prototyping through production deployment and continuous optimization while feeding field insights back to our product and platform engineering teams.
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.
Key Accountabilities:
- Embed with strategic enterprise customers to rapidly diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site.
- 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).
- Ship with full-stack and DevOps depth: Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management.
- Champion observability, monitoring, and telemetry to ensure trustworthy, auditable, and versioned AI agents in production.
- Identify expansion opportunities by working with sales and customer success to uncover high-value use cases across new business domains.
- Feed structured field insights back to Platform Engineering and Product on feature gaps, emerging needs, and usability improvements.
- 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.
Preferred Qualifications:
- 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.
- Experience building agentic AI solutions: multi-agent systems, tool use, and autonomous workflow orchestration.
- Familiarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware).
- Foundry certifications from Palantir/Uniphore or AI/ML-related certifications.
- 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.
Required Qualifications:
- BS/MS/PhD in Computer Science, Data Science, Engineering, Mathematics, Physics, or related field.
- 10+ years in software engineering, data engineering, or AI/ML delivery; at least 4+ years in customer-facing or field roles.
- Proven track record in building and deploying AI/ML applications in production at enterprise scale.
- Deep full-stack proficiency: Python (required), Node.js/Go, React/Vue, SQL/NoSQL databases.
- Hands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks.
- Strong DevOps skills: Docker, Kubernetes, CI/CD, GPU infrastructure, cloud-native deployment patterns.
- 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.
- Willingness to travel up to 25% for on-site customer engagements.
#LI-Remote
#LI-AS
Top Skills
Python,Node.Js,Go,React,Vue,Sql,Nosql,Docker,Kubernetes,Ci/Cd,Gpu Infrastructure (Nvidia H100,B200),Infiniband,Openstack,Vmware,Pinecone,Weaviate,Astradb,Vector Databases,Llms,Prompt Engineering,Rag,Llamaindex,Haystack,Langchain,Langgraph,Crewai,Etl,Elt,Gpu Cluster Management,Erp/Crm Integration,Data Warehouses,Data Lakes
Similar Jobs
Automotive • Hardware • Internet of Things • Mobile • Software • App development • PropTech
As a Field Sales Engineer, you will support the sales team with technical expertise, conduct demonstrations, engage with customers, and collaborate internally to enhance product promotion and sales.
Top Skills:
Access Control SystemsGate OperatorsMyq Community Saas
Big Data • Fintech • Information Technology • Business Intelligence • Financial Services • Cybersecurity • Big Data Analytics
Manage and grow financial-services client accounts: collaborate with Client Executive and product teams, update Salesforce, support product implementation, communicate with users, identify upsell/cross-sell opportunities, gather user feedback, and ensure accurate account information and reporting.
Top Skills:
Salesforce
Automotive • Big Data • Insurance • Software • Transportation
As a Remote Response Associate, you will provide support for customers in roadside emergencies, dispatch service providers, and manage high-stress situations with empathy and effective communication.
Top Skills:
Google WorkspaceZoom
What you need to know about the Charlotte Tech Scene
Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
