Jobs at AuxoAI

Lead AuxoAI’s US brand and ecosystem marketing engine across Google Cloud and AWS partnerships. Own partner co-marketing, field events, earned media, PR, executive speaker programs, thought leadership, and influencer engagement. Build pipeline and market credibility while managing the India-based content and design team, aligning creative output with US partner and field priorities. Track brand visibility, media impact, event ROI, partner marketing performance, and content quality.

The MicroStrategy Developer is responsible for BI application management, including developing dashboards, collaborating with stakeholders, and optimizing performance using MicroStrategy.

Develop and execute AI strategies for clients, assess AI opportunities, lead projects end-to-end, collaborate cross-functionally, advise clients, and provide thought leadership on AI and analytics.

Develop and drive AI strategies for clients by identifying AI use cases, conducting assessments, collaborating with cross-functional teams, and leading projects to deliver measurable business outcomes across sales, marketing, and customer experience.

Lead enterprise AI transformation engagements on Google Cloud. Design scalable AI, machine learning, data, and cloud-native architectures using Gemini Enterprise, Vertex AI, BigQuery, GKE, Cloud Run, and AlloyDB. Conduct customer strategy workshops, guide architecture governance, partner with sales and delivery teams, and advise enterprise stakeholders on secure production deployment and Google Cloud adoption.

Lead enterprise data modernization across Databricks, Snowflake, and AWS. Define target-state architectures, Medallion data models, governance frameworks, CI/CD pipelines, and scalable batch, streaming, and CDC ingestion. Build secure, high-performance data foundations for analytics, machine learning, and Generative AI, including vector storage and feature layers. Establish architecture standards, optimize platform performance, collaborate across technical teams, and advise clients on data strategy and roadmaps.

Design, build, and maintain scalable AWS-based data pipelines and ETL processes. Collaborate with data scientists and analysts to support analytics and ML, optimize storage and query performance, enforce data governance and security, troubleshoot pipelines, and recommend new data engineering solutions.

Lead enterprise AI transformation on Google Cloud: run strategy workshops, design AI-native architectures (Gemini, Vertex AI, BigQuery), build scalable cloud-native platforms (GKE, Cloud Run, AlloyDB), partner with sales and delivery, provide technical leadership and governance to accelerate enterprise AI adoption.

Lead design and delivery of enterprise AI solutions on AWS: architect production-grade AI platforms, create reusable reference architectures and accelerators, run executive workshops, support strategic sales pursuits, mentor engineering teams, and collaborate with frontend and delivery teams across large-scale transformations.

Lead and expand strategic Global 2000 and Fortune 500 accounts by driving AI-enabled data modernization and transformation. Build executive relationships, generate pipeline, close large consulting engagements, coordinate with hyperscalers and partners, and achieve annual bookings and revenue targets.

Own and grow a regional territory by expanding strategic Fortune 500 accounts and developing new Global 2000 customers. Lead executive engagements and complex AI/cloud transformation pursuits, drive pipeline generation, revenue/bookings, and joint GTM with hyperscalers and ecosystem partners. Partner with solution architects, delivery teams, and partners to close large consulting and transformation deals.

Lead and grow a regional enterprise sales territory by expanding strategic Fortune 500 and Global 2000 accounts. Drive AI transformation conversations, new logo acquisition, partner GTM with hyperscalers, and close large consulting and transformation engagements while collaborating with solution architects and delivery teams to meet annual bookings and revenue targets.

Design, build, and maintain scalable AWS-based data pipelines and ETL processes. Collaborate with data scientists, optimize storage and retrieval for performance and cost, enforce data governance and security, troubleshoot pipeline issues, and recommend new data engineering technologies.

Lead and own major client workstreams translating business strategy into AI-enabled solutions. Build stakeholder relationships, design technical approaches, partner with engineers, prototype and deliver AI/data products, mentor junior consultants, and drive measurable business outcomes.

Lead client engagements to define and execute AI strategies, assess AI opportunities, and deliver multi-agent AI solutions across functions. Manage cross-functional teams, ensure project delivery, build client relationships, and translate complex AI concepts for business stakeholders to drive measurable outcomes.

Lead enterprise sales for AI, cloud, and data transformation across Fortune 500 and Global 2000 accounts. Own a regional territory, expand 3-4 strategic accounts, acquire new logos, drive pipeline and annual bookings, build C-suite relationships, coordinate with hyperscalers and partners, and lead complex AI consulting and transformation pursuits.

Lead AI product strategy and delivery for Marketing & Sales, translating GTM problems into scalable AI solutions. Manage executive client relationships, prioritize initiatives, and coordinate cross-functional teams to deliver AI capabilities (MMM, MTA, customer 360, pipeline forecasting, next-best-action). Mentor teams, drive adoption, build governance and success metrics, and contribute to practice growth.

The Senior Data Scientist will lead ML system design and deployment, mentor junior members, and integrate AI models into business applications.

The Full Stack Engineer will develop and maintain scalable web applications, design system architecture, optimize performance, and collaborate with teams for code reviews in a hybrid work environment.

Design and build high-performance, accessible frontend applications with React, TypeScript, and Next.js; develop backend services and APIs with Node.js; integrate cloud infrastructure, containerized deployments, CI/CD, and AI services; establish engineering best practices and mentor peers.