Jobs at Netomi

The Channel Co-Sell Director drives revenue through partner ecosystems and marketplaces, ensuring effective co-selling and enablement programs for cloud transactions and partnerships.

The Partner Enablement Manager builds and scales partner training, certification, and activation programs to enhance partner engagement and revenue growth.

Build scalable data pipelines and ETL/ELT processes using modern data platforms. Perform exploratory analysis, validate data, develop models supporting analytics and real-time insights, and collaborate with data science, product, engineering, and customer success teams. Write tested Python code, contribute to data quality initiatives, and deliver end-to-end features in an agile environment.

Build scalable data pipelines and ETL/ELT processes using Python and modern data platforms. Perform exploratory analysis, validate data, develop data models, and support analytics and real-time insights. Collaborate with data scientists, analysts, engineers, and product teams while delivering tested, reliable features. The role also contributes to data quality policies, processes, scorecards, and product operations reporting.

Build and maintain scalable, responsive frontend applications and key UI modules. Translate designs into high-quality code, create reusable components and libraries, own frontend build and testing systems, ensure UI/UX feasibility, collaborate with backend, data science, and DevOps teams on APIs, and optimize application performance and scalability.

Own a portfolio of strategic enterprise customers from implementation through renewal. Build success plans, manage adoption and value realization, engage executives, forecast renewals, mitigate churn risk, and identify expansion opportunities with Account Management. Lead business reviews, roadmap discussions, customer escalations, and cross-functional coordination. Translate customer feedback into product priorities and advise executives on agentic AI, generative AI, and enterprise CX opportunities and risks.

Owns strategic enterprise accounts, driving retention, renewals, expansion, executive alignment, and measurable ROI for AI deployments. Leads multi-year technical and business roadmaps, complex implementation programs, stakeholder engagement, risk resolution, and executive presentations across Fortune 500 organizations. Requires strong commercial, CX, contact center, technical integration, negotiation, and influencing skills without direct authority. Frequent client-site travel is expected.

Build and optimize production-grade agentic AI systems for marketing and enterprise customer experience use cases. Responsibilities include agent orchestration, tool use, RAG, embeddings, guardrails, LLM evaluation, observability, performance optimization, and scalable Python services deployed on AWS. The role partners across product and engineering teams and requires hands-on experience with LLM agents, marketing data platforms, retrieval systems, and AI evaluation.

Build and scale agentic AI workflows on a no-code platform by designing LLM prompts, integrating REST APIs/webhooks, implementing tests, and applying resilient system design patterns to deliver production-grade autonomous agent solutions.

Drive revenue through enterprise deals as a Partner Solutions Architect, enabling partners, leading POCs, and designing scalable architectures for Netomi's AI platform.

Build and scale agentic workflows and tools using Netomi’s no-code platform. Design LLM prompts, integrate APIs, implement testing and resilient system patterns, troubleshoot workflows, and optimize AI agents for reliability, performance, cost, and fault tolerance. Collaborate with Product, QA, and Delivery teams to deliver production-grade agentic solutions.

Design and implement agentic AI workflows and prototypes on the Netomi platform, integrate generative AI with APIs and cloud services, craft prompts and orchestration chains, partner with sales to scope solutions, present technical designs to stakeholders, and feed customer insights into product and engineering.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

Lead discovery with enterprise customers to design and deploy agentic AI solutions. Define architectures, integration blueprints, workflows, guardrails, and analytics. Own integration design, validate behavior with QA, guide deployments, train stakeholders, and drive reusable templates and continuous improvement across cross-functional teams.

Design, optimize, test, and benchmark prompts and agent tool descriptions to improve AI performance. Collaborate with Customer Success and Data Science, automate evaluation and testing, document prompt practices, and research new NLP and model-specific prompting strategies.

As a Senior Data Analyst, you will analyze large datasets to support machine learning models, optimize AI implementations, and drive performance improvements. Responsibilities include data analysis, client onboarding, and working with cross-functional teams to enhance AI solutions.

Own technical architecture and post-sales success for large, multi-brand enterprise accounts using agentic LLM systems. Design integrations, guardrails, observability, and expansion roadmaps across channels (chat, email, voice, SMS). Drive technical adoption, mentor architects, certify partner delivery, run technical reviews, and translate field learnings into product and prescriptive playbooks.

Lead architecture and quality for enterprise agentic AI deployments across channels and accounts. Define integration, governance, observability, evaluation, and expansion roadmaps. Act as senior technical advisor to customers and partners, translate field evidence into product input, lead escalations, and create prescriptive playbooks and standards for the Customer Architect function.

Build and maintain frontend UI modules for an analytics-focused team: translate designs into reusable components, own build/test systems, integrate with backend/Data Science/DevOps APIs, and optimize for performance and scalability.

Conduct formative and validation UX research for an enterprise agentic AI platform: recruit customers, run interviews and usability tests, synthesize findings, build repeatable research practices, and influence product and design decisions.