Palantir Deployment Engineer

AMroute LLC; Town of Texas (WI); Hybrid; USD 180,000 - 270,000; Full time

Job summary

AMroute LLC is seeking Senior or Principal Forward Deployed Engineer with Palantir Foundry experience to architect, build, and deploy AI solutions for enterprise customers. This role blends deep engineering with business insight, acting as the technical bridge between AI platform capabilities and customer challenges.

You will own the full solution lifecycle from discovery through production deployment, with 25% travel and optional remote work. 100% remote is possible for some engagements.

Qualifications

• Palantir certification is required.
• 6+ years in software engineering, data engineering, or AI/ML delivery; at least 4+ years in customer-facing roles.
• Proven enterprise AI deployment experience in production at scale.
• Hands-on with LLMs, vector databases, data pipelines, RAG pipelines, and agent orchestration frameworks.
• Strong DevOps skills: Docker, Kubernetes, CI/CD, GPU infra, cloud-native deployment.
• Experience integrating ERP, data warehouses, data lakes, and streaming architectures.
• Excellent communication with C-suite and cross-functional teams.
• Experience with Palantir Foundry, AIP, ontology modeling, or similar Enterprise AI platforms.
• Knowledge graphs and ontology modeling expertise.

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, and knowledge graphs.
• Drive rapid prototyping and POCs showing business value within days to weeks.
• Own the full project lifecycle from scoping to post-launch optimization.
• Architect production-grade Enterprise AI apps on Foundry or private cloud with GPU infrastructure.
• Build scalable data pipelines across structured and unstructured data using ETL/ELT and vector DBs.
• Develop and fine-tune LLM/SLM solutions; implement RAG architectures and multi-agent orchestration.
• Deliver full-stack and DevOps depth: Python, Node/Go, React/Vue, Docker, Kubernetes, CI/CD, GPU management.
• Ensure observability, monitoring, and auditable AI agents in production.
• Identify expansion opportunities with sales to span new domains.
• Provide feedback to Platform Engineering on gaps and needs.
• Create reusable IP through architectures, accelerators, and best practices.
• Mentor engineers and customer teams, driving knowledge transfer.

Skills

Palantir Foundry

LLM/SLM delivery

Prompt engineering

Agent orchestration

Multi-agent systems

DevOps (Docker/Kubernetes)

CI/CD

GPU infrastructure

Knowledge graphs

Enterprise AI platforms

Tools

Docker

Kubernetes

CI/CD

Pinecone

Weaviate

AstraDB

LangChain

LangGraph

CrewAI

Haystack

LlamaIndex

Job description

Location: Onsite: Remote - 25% Travel (Preferably in Texas but not a requirement

Senior or Principal level resources, they must have Palantir foundry experience and certifications.

Job Summary:

As a Forward Deployed Engineer FDE), 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.

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.
• 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.

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.