Solutions Architect, Forward Deployed

Rackspace Technology

37d • $152,852 - $269,088 • Hybrid

About The Position

As a Solutions Architect, Forward Deployed at Rackspace Technology, you sit at the front of the sales motion and win business by building. You embed directly with our most strategic enterprise customers to diagnose high-value business problems, co-design AI solutions on-site, and prove them out with working prototypes; not slideware. This is a presales role for someone with an engineering and problem-solving mindset: you own the technical win, and you get there by shipping demonstrable value in days and weeks rather than quarters.
You are platform-first. Your primary craft is enterprise AI development platforms; Palantir Foundry and AIP, and AWS Bedrock/Agent Core, deployed on Rackspace Private Cloud, GPU infrastructure, or the customer's AWS cloud. Cloud services are the substrate you build on, not the product you lead with.
The role combines deep technical engineering with commercial instinct, customer empathy, and end-to-end ownership of the technical narrative from first conversation through signed Statement of Work and delivery handoff. It suits someone who wants the autonomy and immediacy of an AI startup, backed by the scale, partner relationships, and delivery bench of a global technology company.

Requirements

• A bachelor's degree in computer science, data science, engineering, mathematics, or a related technical field. At the manager's discretion, additional relevant experience may substitute for the degree requirement.
• 10+ years in software engineering, data engineering, or AI/ML delivery, including at least 4 years in customer-facing, presales, or field engineering roles.
• Demonstrated presales or sales engineering track record: owning the technical win, building and delivering demonstrations, and authoring Statements of Work.
• Proven experience designing and delivering enterprise-scale solutions using Palantir Foundry, including data modeling, pipeline development, ontology design, and operational workflows.
• Hands-on expertise with Palantir AIP, including building, deploying, and governing AI-driven applications, workflows, and decision intelligence solutions.
• Proven track record building and deploying AI/ML applications in production at enterprise scale.
• Deep full-stack proficiency: Python (required), plus Node.js/Go, React/Vue, and 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, cloud-native deployment patterns, and familiarity with GPU infrastructure.
• Experience integrating across heterogeneous enterprise systems — ERP, CRM, data warehouses, data lakes, and streaming architectures.
• Working knowledge of at least one hyperscaler's AI and data service portfolio, AWS preferred (Bedrock, SageMaker, Glue, Redshift).
• Ability to translate a customer's business and IT needs into a Statement of Work or Scope Addendum that delineates the need into actionable items.
• Excellent communication skills — comfortable with C-suite presentations, technical workshops, and cross-functional collaboration.
• Ability to travel approximately 25%.
• Unrestricted right to work in the US without requiring sponsorship.

Nice To Haves

• Palantir certification (Foundry Foundations, Data Engineer, or AIP) — strongly preferred, or the ability to certify within 90 days of hire.
• AWS Certified Solution Architect — required or the ability to certify within 90 days of hire.
• An advanced degree (master's or PhD) in a relevant field.
• Prior experience in technology consulting, AI startups, or Forward Deployed / Solutions Engineering roles.
• Experience with knowledge graphs, semantic modeling, and ontology-driven data management.
• 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.
• Hands-on experience across multiple lakehouse platforms (Databricks, Snowflake, AWS-native Glue + Athena + Redshift) and multiple AI platforms (Amazon Bedrock, Azure OpenAI, Google Vertex AI).
• Experience with AWS professional services or the AWS partner ecosystem across both AI and data domains.
• Familiarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware).
• Industry certifications: AWS Solutions Architect Professional, Machine Learning Engineer, or Data Analytics; Databricks Certified; Snowflake SnowPro.
• Experience in regulated industries requiring governance for both AI and data platforms.
• Domain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing.
• Published thought leadership in enterprise AI applications or modern data architectures.

Responsibilities

• Drive top-of-funnel opportunity creation with sales, account teams, and partner alliances — opening executive conversations with working demonstrations of what is possible on our platforms.
• Lead on-site discovery: diagnose critical business challenges, map the customer's data landscape, and co-design AI solutions with business and technical stakeholders in the room.
• Own the technical narrative across the sales cycle; art-of-the-possible sessions, architecture workshops, platform evaluations and bake-offs, security and governance deep dives, and executive briefings.
• Translate customer business and IT needs into Statements of Work and Scope that delineate the need into a set of actionable, estimable work packages.
• Develop business cases and ROI models that connect AI ambition to the data foundation work required to support it, so the commercial case survives procurement scrutiny.
• Identify expansion opportunities across new business domains, working with sales and customer success to surface high-value use cases in accounts already live.
• Hand off to delivery cleanly; architecture, assumptions, dependencies, risks, and success criteria documented; and stay engaged as technical advisor through mobilization.
• Build rapid proofs of concept and working prototypes that demonstrate tangible business value within days to weeks.
• Design and demonstrate agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications against the customer's own data wherever possible.
• Architect production-grade enterprise AI applications on partner platforms, Rackspace Private Cloud, and GPU infrastructure, integrating with enterprise systems including ERP, CRM, data warehouses, and data lakes.
• Design ontologies and semantic models that make heterogeneous enterprise data usable by AI agents and operational workflows.
• Build demonstration data pipelines across structured and unstructured sources using ETL/ELT patterns, vector databases, and knowledge base frameworks.
• Build prototypes with enough engineering discipline to survive customer security and architecture review — versioned, observable, auditable, and evaluated.
• Maintain and extend a library of reusable demo assets, accelerators, and sandbox environments so the next pursuit starts further down the field.
• Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that make future engagements faster and more repeatable.
• Mentor Solution Architects and solutions engineers, guiding technical development and growing bench strength across partner platforms and AI solution patterns.
• Feed structured field insights back to Platform Engineering, Product, and partner alliance teams on feature gaps, emerging customer needs, and usability improvements.
• Contribute thought leadership — reference architectures, published writing, conference and partner-event content — that establishes Rackspace's credibility in enterprise AI.

Benefits

• annual bonus or incentives
• equity awards
• Employee Stock Purchase Plan (ESPP)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior