Forward Deployed Engineer

FORWARD DEPLOYED ENGINEER 

Job Summary:  

As a Forward Deployed Engineer 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. 

Work Location/Travel: 

• You may work 100% remotely. 

• Travel up to 25% for on-site customer engagements. 

Key Responsibilities: 

• 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. 

Required Qualifications: 

• Must be Palantir certified. 

• 6+ 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 

FORWARD DEPLOYED ENGINEER - Palantir

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.