Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments.
Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.
As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.
Job Description:
Senior Technical Product Manager - AI Platform (SLM, RLHF & ML-Ops)
About Uniphore:
Uniphore is one of the largest B2B AI-native companies with decades of proven, built for scale, and designed for the enterprise. Our Business AI Cloud (BAIC) powers mission-critical AI deployments for Fortune 500 customers across regulated and data-intensive industries.
Uniphore’s platform uniquely combines Generative AI, Knowledge AI, Emotion AI, multimodal understanding, and guided workflows to deliver trustworthy, explainable, and outcome-driven enterprise AI. We operate at production scale—across voice, video, text, and structured data—where reliability, governance, and performance matter as much as innovation.
Why This Role Matters:
Enterprise GenAI is moving beyond prompts and demos. Customers now demand:
- Private, fine-tuned domain specific models (SLMs)
- Human-in-the-loop learning (RLHF) with business user inputs
- Production-grade evaluation, governance, and observability
- Repeatable and production grade ML-Ops pipelines, not science projects
This role owns the core AI platform knowledge capabilities that make all of that real.
Role Overview:
We are hiring a Senior Technical AI Product Manager to build and scale core AI platform features that enable:
- SLM fine-tuning & adaptation
- RLHF / RHFL workflows
- Model evaluation & quality measurement
- Enterprise-grade ML Ops and inference lifecycle management
You will operate at the intersection of model / data science, platform engineering, and enterprise product delivery, owning foundational capabilities used by multiple product teams internally (BAIS) as well as external enterprise customers (BAIC).
This is a deeply technical platform PM role, ideal for someone who has worked closely with ML engineers, data scientists, and infra teams and knows how to turn complex AI systems into reliable, scalable, and consumable enterprise platforms.
What You’ll Own
- Own the end-to-end product roadmap for SLM fine-tuning, RLHF, evals, and ML-Ops capabilities within BAIC
- Work daily with ML engineers, platform engineers, applied scientists, and UX
- Translate advanced AI capabilities into clear platform abstractions and APIs
- Engage directly with strategic enterprise customers and design partners
- Drive build-vs-buy decisions and ecosystem integrations
- Define standardized, repeatable workflows for model adaptation.
- Productize private model training and adaptation for enterprise customers with strong isolation, governance, and IP protection
- Lead platform support for PEFT-based fine-tuning (LoRA, QLoRA, adapters)
- Enable human-in-the-loop learning (RLHF / RHFL) including feedback collection, labeling pipelines, and reward modeling
- Define and ship Eval frameworks, training, continuous fine-tuning to enable agentic workflows.
- Operationalize trust, explainability, scale, and cost efficiency by partnering with internal and external stakeholders.
Required Qualifications
- 5+ years of technical product management experience, with significant focus on AI/ML platforms or infrastructure
- Hands-on experience shipping products involving LLMs / SLMs, fine-tuning, RAG, or ML pipelines
- Strong understanding of:
- SLM fine-tuning techniques (PEFT, LoRA, QLoRA)
- RLHF / RHFL concepts and workflows
- Model evaluation methodologies
- Experience working closely with ML, data science, and infra teams
- Ability to reason about systems, tradeoffs, and abstractions, not just features
- Strong written and verbal communication for technical and executive audiences\
Preferred Qualifications
- Experience building or managing MLOps platforms (training, deployment, monitoring)
- Familiarity with tools such as PyTorch, LangChain, Kubeflow, Arize, Weights & Biases
- Experience with enterprise knowledge systems, vector databases, or Graph-based RAG
- Background in data science, ML engineering, or applied AI
- Experience shipping AI platforms for regulated or Fortune-500 environments
Hiring Range:
The specific rate will depend on the successful candidate's qualifications and prior experience.
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.
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.
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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.









