Senior Forward Deployed Engineer – Palantir Certified

Rackspace Technology

4d • $165,830 - $243,142 • Remote

About The Position

As a Senior Forward Deployed Engineer at Rackspace Technology, you will work directly with strategic enterprise customers to architect, build, and deploy AI solutions. The role combines engineering, business acumen, customer engagement, and end-to-end solution ownership. You will bridge Rackspace’s AI platform capabilities and customers’ business challenges, owning solutions from discovery and prototyping through production deployment and ongoing optimization. You will also share field insights with product and platform engineering teams.

The position is remote, with work from home and approximately 25% travel for on-site customer engagements. It focuses on designing and delivering enterprise AI applications and workflows, integrating with enterprise systems, building data pipelines, and deploying and monitoring production AI solutions. The role also involves identifying opportunities with customers, developing reusable technical assets, and mentoring engineers and customer teams.

Requirements

• Palantir certification is required.
• At least 6 years of experience in software engineering, data engineering, or AI/ML delivery, including at least 4 years in customer-facing or field roles.
• Proven track record building and deploying production AI/ML applications at enterprise scale.
• Deep full-stack proficiency, including Python (required), Node.js/Go, React/Vue, and 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, including Docker, Kubernetes, CI/CD, GPU infrastructure, and cloud-native deployment patterns.
• Experience integrating heterogeneous enterprise systems, including ERP systems, data warehouses, data lakes, and streaming architectures.
• Ability to translate ambiguous customer needs into actionable engineering plans under tight timelines.
• Excellent communication skills, including comfort with C-suite presentations, technical workshops, and cross-functional collaboration.

Nice To Haves

• 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 such as NVIDIA H100/B200 and InfiniBand, and private cloud platforms such as OpenStack or 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.

Responsibilities

• Diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site.
• Lead end-to-end design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.
• Build rapid prototypes and proofs of concept that demonstrate business value within days to weeks.
• Own the full project lifecycle, including scoping, architecture, development, 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 such as ERP, CRM, data warehouses, and data lakes.
• Build scalable data pipelines for 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 technologies including Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management.
• Champion observability, monitoring, and telemetry to support trustworthy, auditable, and versioned AI agents in production.
• Work with sales and customer success to identify expansion opportunities and high-value use cases across business domains.
• Provide structured field insights to Platform Engineering and Product about feature gaps, emerging needs, and usability improvements.
• Create reusable intellectual property, including reference architectures, accelerators, frameworks, and technical best practices.
• Mentor engineers and customer teams, transfer knowledge, and help build internal AI competencies.

Benefits

• The compensation package may include annual bonus or incentive opportunities, equity awards, and an Employee Stock Purchase Plan (ESPP).
• Rackspace states that benefits are available and provides a link to learn more, but specific benefits are not listed in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed