{"id":193890,"url":"https://alion.io/job/rackspace-technology-solutions-architect-forward-deployed","title":"Solutions Architect, Forward Deployed","company":{"id":46166,"name":"Rackspace Technology","domain":"rackspace.com","url":"https://alion.io/company/rackspace","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":86,"open_postings":7,"ghost_share":0.143,"stale_share":0.143,"repost_share":0.143,"time_to_fill_p50_days":28,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":152852,"max":269087,"currency":"USD","period":"year","gross":null,"usd_annual":269087},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Glue","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Haystack","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Node JS","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Vue.js","optional":false},{"name":"Weaviate","optional":false},{"name":"Azure","optional":true},{"name":"Function Calling","optional":true},{"name":"InfiniBand","optional":true},{"name":"JavaScript","optional":true},{"name":"Machine Learning","optional":true},{"name":"OpenAI","optional":true},{"name":"OpenStack","optional":true},{"name":"RLHF","optional":true},{"name":"Vertex AI","optional":true},{"name":"VMWare","optional":true}],"status":"live","first_seen_at":"2026-09-02T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-25T07:52:05Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":53},"description":"Job Summary\nAs 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.\nYou 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.\nThe 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.\nWork Location and Travel\nCandidates who live in the San Antonio, TX area work a hybrid schedule with two days in the office.\n\nIf not located near San Antonio, you may work 100% from home.\n\nTravel up to 50% per business requirements, for on-site customer engagements, workshops, and partner and hyperscaler events.\n\n\"Work from home postings are limited to candidates residing within the country specified in the posting location.\"\nSponsorship\nThis role is not sponsorship eligible.\nCandidates need to be legally allowed to work in the US for any employer.\nKey Responsibilities\nOpportunity Creation and Presales Leadership\nDrive 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.\nLead 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.\nOwn 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.\nTranslate customer business and IT needs into Statements of Work and Scope that delineate the need into a set of actionable, estimable work packages.\nDevelop 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.\nIdentify expansion opportunities across new business domains, working with sales and customer success to surface high-value use cases in accounts already live.\nHand off to delivery cleanly;architecture, assumptions, dependencies, risks, and success criteria documented; and stay engaged as technical advisor through mobilization.\nSolution Design, Prototyping, and Demonstration\nBuild rapid proofs of concept and working prototypes that demonstrate tangible business value within days to weeks.\nDesign and demonstrate agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications against the customer's own data wherever possible.\nArchitect 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.\nDesign ontologies and semantic models that make heterogeneous enterprise data usable by AI agents and operational workflows.\nBuild demonstration data pipelines across structured and unstructured sources using ETL/ELT patterns, vector databases, and knowledge base frameworks.\nBuild prototypes with enough engineering discipline to survive customer security and architecture review - versioned, observable, auditable, and evaluated.\nMaintain and extend a library of reusable demo assets, accelerators, and sandbox environments so the next pursuit starts further down the field.\nTechnical Depth: Platform First, Cloud Second\nPalantir Foundry and AIP - maintain deep, current, hands-on expertise across data modeling, pipeline development, ontology design, operational workflows, and the build, deployment, and governance of AI-driven applications and decision intelligence solutions.\n AI and LLM engineering - prompt engineering, fine-tuning, model distillation, RAG implementation (LlamaIndex, Haystack), multi-agent orchestration (LangChain, LangGraph, CrewAI), vector databases (Pinecone, Weaviate, AstraDB), and AI evaluation frameworks.\nAWS as deployment substrate - working fluency in the AWS AI and data services that underpin platform deployments: Amazon Bedrock, Amazon Q, SageMaker including Unified Studio, AWS Glue, Redshift, EMR, QuickSight with Q, plus Databricks on AWS, Snowflake on AWS, Apache Iceberg, and Delta Lake.\nFull-stack and DevOps - Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and working familiarity with GPU cluster management - enough to build and stand up your own demos without waiting on a delivery team.\nArchitectural judgment - guide build versus buy decisions across both AI capabilities and data platform components, and stay current on foundation models, agentic patterns, lakehouse architectures, and data mesh.\nEnablement, Intellectual Property, and Field Feedback\nBuild reusable IP through reference architectures, accelerators, frameworks, and technical best practices that make future engagements faster and more repeatable.\nMentor Solution Architects and solutions engineers, guiding technical development and growing bench strength across partner platforms and AI solution patterns.\nFeed structured field insights back to Platform Engineering, Product, and partner alliance teams on feature gaps, emerging customer needs, and usability improvements.\nContribute thought leadership - reference architectures, published writing, conference and partner-event content - that establishes Rackspace's credibility in enterprise AI.\nDNA of a Successful Solutions Architect, Forward Deployed\nComfortable being the most technical person in a commercial conversation and the most commercially aware person in a technical one.\nInnately service-oriented; always communicates with respect and professionalism.\nA builder by instinct - reaches for a prototype before a slide when a customer asks whether something is possible.\nMotivated self-starter who takes ownership of customer needs and works to a positive outcome that yields high customer service levels.\nTrusted advisor who conducts deep-dive sessions to help customers overcome adoption, security, and governance concerns.\nExcellent problem-solving, analytical, presentation, and whiteboarding skills.\nTranslates ambiguous customer needs into actionable engineering plans under tight timelines.\nPrioritizes deals, training, and internal initiatives through highly effective time management.\nInteracts in an engaging way with individuals and groups, conveying the value of Rackspace services with clarity on the benefit to the customer.\nRequired Qualifications\nA 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.\n10+ years in software engineering, data engineering, or AI/ML delivery, including at least 4 years in customer-facing, presales, or field engineering roles.\nDemonstrated presales or sales engineering track record: owning the technical win, building and delivering demonstrations, and authoring Statements of Work.\nProven experience designing and delivering enterprise-scale solutions using Palantir Foundry, including data modeling, pipeline development, ontology design, and operational workflows.\nHands-on expertise with Palantir AIP, including building, deploying, and governing AI-driven applications, workflows, and decision intelligence solutions.\nProven track record building and deploying AI/ML applications in production at enterprise scale.\nDeep full-stack proficiency: Python (required), plus Node.js/Go, React/Vue, and SQL/NoSQL databases.\nHands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks.\nStrong DevOps skills: Docker, Kubernetes, CI/CD, cloud-native deployment patterns, and familiarity with GPU infrastructure.\nExperience integrating across heterogeneous enterprise systems - ERP, CRM, data warehouses, data lakes, and streaming architectures.\nWorking knowledge of at least one hyperscaler's AI and data service portfolio, AWS preferred (Bedrock, SageMaker, Glue, Redshift).\nAbility to translate a customer's business and IT needs into a Statement of Work or Scope Addendum that delineates the need into actionable items.\nExcellent communication skills - comfortable with C-suite presentations, technical workshops, and cross-functional collaboration.\nAbility to travel approximately 25%.\nUnrestricted right to work in the US without requiring sponsorship.\nPreferred Qualifications\nPalantir certification (Foundry Foundations, Data Engineer, or AIP) - strongly preferred, or the ability to certify within 90 days of hire.\nAWS Certified Solution Architect - required or the ability to certify within 90 days of hire.\nAn advanced degree (master's or PhD) in a relevant field.\nPrior experience in technology consulting, AI startups, or Forward Deployed / Solutions Engineering roles.\nExperience with knowledge graphs, semantic modeling, and ontology-driven data management.\nKnowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.\nExperience building agentic AI solutions: multi-agent systems, tool use, and autonomous workflow orchestration.\nHands-on experience across multiple lakehouse platforms (Databricks, Snowflake, AWS-native Glue + Athena + Redshift) and multiple AI platforms (Amazon Bedrock, Azure OpenAI, Google Vertex AI).\nExperience with AWS professional services or the AWS partner ecosystem across both AI and data domains.\nFamiliarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware).\nIndustry certifications: AWS Solutions Architect Professional, Machine Learning Engineer, or Data Analytics; Databricks Certified; Snowflake SnowPro.\nExperience in regulated industries requiring governance for both AI and data platforms.\nDomain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing.\nPublished thought leadership in enterprise AI applications or modern data architectures.\n#LI-AW1\n#LI-Remote\n\nOur compensation reflects the cost of labor across several geographic markets. The compensation range for this position ranges from $152,852.00/year in our lowest geographic market up to 269,087.50 USD/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives, equity awards and an Employee Stock Purchase Plan (ESPP). Learn more about benefits at Rackspace.\n\nAbout Rackspace Technology\nWe are the multicloud solutions experts. We combine our expertise with the world’s leading technologies - across applications, data and security - to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. 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