Forward Deployed Engineer IV - US

Pace Industries, LLC; United States; Hybrid; USD 132,149 - 193,856; Full time

Job summary

Rackspace Technology is seeking a Forward Deployed Engineer to be embedded with enterprise customers to architect, build, and deploy high‑impact AI solutions. You serve as the technical bridge between Rackspace’s AI platform and the customer’s business challenges, owning the full solution lifecycle from problem discovery, rapid prototyping, production deployment, to continuous optimization.

Location and travel: if in San Antonio, TX you’ll work a hybrid schedule; elsewhere you may work 100%

Qualifications

• Bachelor’s degree in computer science or related discipline or equivalent experience.
• Proven track record in building and deploying AI/ML applications in production at enterprise scale.
• Hands‑on with LLMs, vector databases, data pipelines, and agent orchestration frameworks.
• Strong DevOps skills: Docker, Kubernetes, CI/CD, GPU infrastructure.

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 and RAG pipelines.
• Drive rapid prototyping and POCs with measurable business value.
• Own the full project lifecycle: scoping, architecture, build, deployment, and optimization.
• Architect production‑grade AI applications and integrate with ERP/CRM/data lakes.
• Build scalable data pipelines across structured and unstructured data.
• Develop and fine‑tune LLM/SLM solutions and orchestrate multi‑agent workflows.
• Ensure observability, monitoring, and governance of AI agents in production.
• Mentor engineers and customer teams, sharing best practices and insights.

Skills

Python

LLMs

Prompt engineering

Kubernetes

Docker

CI/CD

Cloud

Data engineering

SQL/NoSQL

English comms

Education

Bachelor’s degree in computer science or related

Tools

Palantir Foundry

AIP

LangChain

Weaviate

Pinecone

Haystack

OpenStack

VMware

NVIDIA GPUs

Job description

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. You serve as the technical bridge between Rackspace’s AI platform capabilities and the customer’s most pressing business challenges, owning the full solution lifecycle from problem discovery, rapid prototyping, production deployment, to continuous optimization, while feeding field insights back to our product and platform engineering teams.

Location and Travel

If located in San Antonio, TX, you’ll work a hybrid schedule with 2 days in our office and three days remotely. If located elsewhere, you may work 100% remotely. Willingness to travel up to 25% for on‑site customer engagements is required.

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

• Bachelor’s degree in computer science, engineering, or related discipline required; equivalent experience may substitute.
• 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 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.

Compensation

Compensation ranges from $132,149 to $193,856 per year, based on geographic location. Salary may be supplemented with annual bonus, equity awards, and participation in the Employee Stock Purchase Plan (ESPP).

Legal Notice / Equal Employment Opportunity

We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.