Uniphore is the Business AI company. Our sovereign, composable and secure AI platform connects enterprise data, fine-tunes AI models and deploys agentic AI across the enterprise. We empower every worker to boost productivity and help businesses grow faster, operate smarter and reduce costs. Trusted by more than 2,000 businesses globally, and recognized on the Deloitte Fast 500, Uniphore delivers on the promise of AI as a transformative force for business.
Job Description:
Uniphore is The Business AI Company. We enable businesses to rapidly adopt, significantly transform, and immediately unlock value through AI. Inspired by the simplicity of consumer AI, and with a deep understanding of the scalability and security required for business, we provide a platform that allows business users to effortlessly harness agentic AI, tapping into enterprise knowledge grounded in their own proprietary data.
Through our core principles of composable, sovereign, and secure AI, we are committed to unlocking AI's potential as a transformative force for businesses - with openness, trust, and scalability unmatched by any other solution. Our Business AI Cloud (BAIC) is a complete AI platform to power the Agentic Enterprise: it unifies data, knowledge, models, and agents in a secure, composable stack — enabling business users to deploy AI agents instantly and IT leaders to scale trusted, enterprise-grade applications.
Role Overview
As Enterprise Data Architect within Forward Deployed Engineering, you are the architectural authority for how customer data becomes trustworthy, AI-ready fuel for agentic solutions on the Business AI Cloud. You will partner directly with FDE engineers and enterprise clients to design the data models, integration patterns, and governance standards that ground retrieval, multi-agent orchestration, and SLM/LLM workflows in accurate, compliant, well-structured enterprise data.
This is a hands-on, cross-engagement role: you will move across multiple concurrent customer deployments - spanning source systems such as AWS, GCP, SAP, Salesforce, AS/400, D365, and Outlook/M365 - codifying reusable data architecture patterns rather than solving each integration from scratch. You will also help scale the FDE organization's data maturity, mentoring engineers and building the playbooks that let Uniphore stand up new customer data foundations quickly, securely, and consistently.
Key Responsibilities
Cross-Engagement Data Architecture: Serve as the principal data architecture authority across multiple concurrent FDE customer engagements, ensuring data models, pipelines, and integration designs are scalable, secure, and consistent with BAIC platform standards.
AI-Ready Data Design: Define canonical and dimensional data models, embedding/vector store schemas, and retrieval-grounding data structures that power RAG pipelines, multi-agent orchestration, and SLM/LLM fine-tuning for customer solutions.
Enterprise Integration Leadership: Architect integration patterns across enterprise source systems - AWS, GCP, SAP, Salesforce, AS/400, D365, Outlook/M365, and other ERP/CRM/legacy platforms - establishing connector strategies for both cloud and on-premise environments.
Data Quality & Governance: Establish data quality, lineage, metadata, and governance standards so agentic AI systems operate on validated, auditable data; define observability and monitoring practices for data pipelines feeding production agents.
Reusable Frameworks & Playbooks: Own and extend Uniphore's enterprise integration playbook and data architecture asset library, turning patterns learned on individual engagements into reusable frameworks that accelerate future deployments.
Team Leadership & Mentoring: Mentor FDE engineers on data modeling, ETL/ELT design, and enterprise integration best practices; review and validate data architecture decisions across the FDE portfolio.
Customer & Stakeholder Partnership: Act as a trusted data architecture advisor to senior customer stakeholders, translating ambiguous data landscapes and legacy system constraints into pragmatic, scalable designs.
Build vs. Buy & Tooling Strategy: Evaluate data platform, ETL, and data quality tooling; lead POCs and make build-vs-buy recommendations balancing cost, performance, and time-to-value for customer deployments.
Product & Platform Feedback: Partner with Product and Platform Engineering to feedback connector gaps, data architecture requirements, and customer pain points observed across engagements, shaping the BAIC data layer roadmap.
Compliance & Security: Partner with Security and customer compliance teams to ensure data privacy, encryption, residency, and regulatory requirements are met across regulated industries (e.g., healthcare, financial services).
Qualifications
10+ years of experience in data architecture, data engineering, or enterprise data platform roles, including hands-on design of large-scale, cloud-based data systems.
Deep expertise in data modeling - dimensional modeling, canonical/semantic data models, and ETL/ELT pipeline design - across relational and NoSQL systems.
Hands-on proficiency in SQL and Python; experience with modern cloud data platforms (AWS, Azure, or GCP) and data warehouse/lakehouse technologies (e.g., Snowflake, Databricks).
Proven experience integrating enterprise systems - ERP (SAP), CRM (Salesforce), legacy platforms (AS/400), and Microsoft ecosystems (D365, Outlook/M365) - across cloud and on-premise architectures.
Experience designing data foundations for AI/ML or GenAI use cases, including retrieval-augmented generation, vector databases, and embedding pipelines, strongly preferred.
Track record of establishing data governance, lineage, and quality standards across teams or client engagements.
Prior experience in a client-facing, consulting, or forward-deployed engineering role, translating ambiguous business needs into technical data architecture.
Strong communication skills, with the ability to bridge technical data architecture decisions and business stakeholder priorities.
Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field.
Desired Skills
Exposure to Agentic AI platforms, LLM/SLM fine-tuning, and multi-agent orchestration frameworks (LangChain, LangGraph, CrewAI).
Experience with real-time streaming and messaging frameworks (e.g., Kafka) and CDC-based data ingestion.
Familiarity with data security and compliance frameworks (e.g., HIPAA, PCI-DSS, GDPR, SOX).
Experience with BI/analytics tooling (Tableau, Looker, or similar) for downstream reporting and self-service analytics.
Contributions to industry thought leadership, playbooks, or whitepapers on enterprise data architecture or Agentic AI.
Hiring Range:
$226,100 - $310,900 - for Primary Location of USA - CA - Palo Alto
Hiring Pay Range:
$232,900 - $291,100Benefits:
In addition to competitive base pay, this position also includes an annual incentive opportunity based on target achievement, pre-IPO stock options, benefits including medical, dental, vision, 401(k) with a match, and more, plus generous paid time off, paid holidays, paid day off for your birthday and other paid leave policies to support employees through all phases of life.
Location preference:
Uniphore is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
For more information on how Uniphore uses AI to unify—and humanize—every enterprise experience, please visit www.uniphore.com.
Skills Required
- 10+ years of experience in data architecture, data engineering, or enterprise data platform roles
- Hands-on design experience with large-scale, cloud-based data systems
- Deep expertise in dimensional modeling, canonical or semantic data models, and ETL/ELT pipeline design
- Experience with relational and NoSQL systems
- Hands-on proficiency in SQL and Python
- Experience with modern cloud data platforms such as AWS, Azure, or GCP
- Experience with data warehouse or lakehouse technologies such as Snowflake or Databricks
- Experience integrating ERP, CRM, legacy, and Microsoft ecosystem platforms across cloud and on-premise architectures
- Experience establishing data governance, lineage, and quality standards
- Prior client-facing, consulting, or forward-deployed engineering experience
- Strong communication skills for translating technical architecture decisions to business stakeholders
- Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field
- Experience designing data foundations for AI/ML or GenAI use cases, including RAG, vector databases, and embedding pipelines
- Exposure to agentic AI platforms, LLM/SLM fine-tuning, and multi-agent orchestration frameworks
- Experience with real-time streaming, messaging frameworks, or CDC-based data ingestion
- Familiarity with HIPAA, PCI-DSS, GDPR, or SOX
- Experience with BI and analytics tools such as Tableau or Looker
- Contributions to industry thought leadership, playbooks, or whitepapers
Uniphore Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uniphore and has not been reviewed or approved by Uniphore.
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Healthcare Strength — Health coverage includes medical, dental, vision, mental‑health resources, and wellness programs, with multiple plan options (including HSA/FSA) indicating robust depth. Plan quality and affordability are highlighted relative to peers.
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Leave & Time Off Breadth — Time off includes generous PTO, paid holidays, and a paid birthday day off. Enhanced parental, caregiver, and bereavement leave extend coverage beyond standard policies.
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Retirement Support — Retirement offerings include a U.S. 401(k) with company match and pension/retirement plans with employer contributions in many countries. These programs support longer‑term financial security alongside core pay.
Uniphore Insights
What We Do
The Business AI Cloud is the only sovereign, composable and secure AI platform that enables businesses to rapidly adopt, significantly transform and immediately unlock the value of their data. Trusted by more than 2,500 of the world’s largest enterprises and recognized by Gartner, Forrester, IDC and the Deloitte Fast 500, Uniphore is where enterprise AI moves from ambitions to production. A Complete, Composable Platform Uniphore is designed to be: Sovereign — run on any public cloud, private cloud or on-premises with full control over your data and AI models. Composable — choose your layer, model, or component—vector DBs, knowledge graphs, data compute, and beyond. Secure — embedded guardrails, observability, and AI security ensure trusted, compliant, and enterprise-grade protection. Trusted at Scale Over 2,000 global businesses — including many of the Fortune 500 — rely on Uniphore every day to drive growth, improve efficiency, and deliver personalized customer experiences. Customers include leaders across industries, like Skechers, LastPass, Atlassian, HP, Allstate, Sony, and more. Industry Recognition Named to Inc.'s Best in Business List Listed on the Deloitte Technology Fast 500 Recognized in reports by Gartner, Forrester, and IDC From Pilot to Production Through strategic collaborations with industry leaders like KPMG, Cognizant, Rackspace, Databricks and Snowflake, Uniphore helps organizations move beyond experimental AI pilots to production-grade deployment — operationalizing AI agents across internal and client-facing workflows at scale.
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