Forward Deployed Engineer III

Rackspace Technology

. Diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site .

Posted 10/28/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in architecting and deploying Enterprise AI applications, integrating with enterprise systems, and building scalable data pipelines. Proven ability to lead technical projects, mentor teams, and communicate effectively with stakeholders at all levels.

Highest-signal resume keywords

Palantir CertificationFull-Stack Proficiency: Python, Node.js/Go, React/VueDevOps Skills: Docker, Kubernetes, CI/CDExperience with LLMs and RAG ArchitecturesIntegration of Enterprise Systems: ERP, Data Warehouses, Data Lakes

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonNode.jsGoReactVueSQLNoSQLLLMsRAG PipelinesData Pipelines

Soft Skills

Excellent Communication SkillsCross-Functional CollaborationCustomer-Facing ExperienceMentoring

Tools & Technologies

Palantir FoundryAIPDockerKubernetesGPU InfrastructureOpenStackVMware

Certifications & Qualifications

Palantir Certified

Industry Keywords

Financial ServicesHealthcareSupply ChainDefenseEnergyManufacturing

Tech Stack

Tools & technologies

CloudDockerERPETLJavaScriptKubernetesNode.jsNoSQLOpenStackPythonReactSQLVMwareVue.jsGo

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 proofs of concept demonstrating tangible business value within days to weeks
Serve as primary technical owner across 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
Integrate AI applications with enterprise systems including ERP, CRM, data warehouses, and data lakes
Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases, and knowledge base frameworks
Develop and fine-tune LLM/SLM solutions; implement RAG architectures and orchestrate multi-agent workflows
Deliver full-stack and DevOps solutions using Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management
Champion observability, monitoring, and telemetry for trustworthy, auditable, and versioned AI agents in production
Identify expansion opportunities with sales and customer success across new business domains
Feed field insights 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
Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies

Requirements

What you’ll need

Must be Palantir certified
5+ years in software engineering, data engineering, or AI/ML delivery
At least 4+ years in customer-facing or field roles
Proven track record 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 experience 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, and cloud-native deployment patterns
Experience integrating heterogeneous enterprise systems, including ERP, data warehouses, data lakes, and 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, including multi-agent systems, tool use, and autonomous workflow orchestration
Familiarity with GPU infrastructure, including NVIDIA H100/B200 and InfiniBand, and private cloud platforms such as OpenStack and 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

Equal employment opportunity without regard to legally protected characteristics
Disability or special-needs accommodation available upon request