Senior Forward Deployed Engineer

Rackspace Technology

Sr Forward Deployed Engineer at Rackspace Technology building and deploying high-impact AI solutions. Acting as a technical bridge between AI capabilities and customer challenges.

Posted 7/22/2026full-timeSan Antonio • Texas • 🇺🇸 United StatesSenior💰 $165,830 - $243,141 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and delivering enterprise-scale AI applications, leveraging deep full-stack proficiency in Python, Node.js/Go, and React/Vue. Proven ability to integrate complex data landscapes and drive customer-facing AI/ML solutions with strong DevOps practices and effective communication skills.

Highest-signal resume keywords

Palantir Certification10+ Years in Software Engineering or AI/ML DeliveryDeep Full-Stack Proficiency: Python, Node.js/Go, React/VueStrong DevOps Skills: Docker, Kubernetes, CI/CDExperience with LLMs and Agent Orchestration Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonNode.jsGoReactVueSQLNoSQLLLMsData PipelinesRAG Pipelines

Soft Skills

Excellent Communication SkillsCross-Functional CollaborationCustomer-Facing Experience

Tools & Technologies

Palantir FoundryDockerKubernetesGPU InfrastructureOpenStackVMware

Certifications & Qualifications

Palantir Certified

Industry Keywords

Financial ServicesHealthcareSupply ChainDefenseEnergyManufacturing

Tech Stack

Tools & technologies

CloudDockerERPETLGoJavaScriptKubernetesNode.jsNoSQLOpenStackPythonReactSQLVMwareVue.js

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

Bachelor’s degree in computer science, engineering, or related technical discipline required
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
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
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)
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.

Benefits

Comp & perks

incentive compensation opportunities in the form of annual bonus or incentives
equity awards
Employee Stock Purchase Plan (ESPP)