AI Engagement specialist
GoML
Remote
At GoML, we design and build cutting-edge Generative AI, AI/ML, and Data Engineering solutions that help businesses unlock the full potential of their data, drive intelligent automation, and create transformative AI-powered experiences.
Our mission is to bridge the gap between state-of-the-art AI technology stack and real-world enterprise applications—helping organizations innovate faster, make smarter decisions, and scale production-grade AI solutions seamlessly.
We are looking for an AI Engagement Specialist to own and grow relationships with our key customers. In this role, you will combine Customer Success, Account Management, and engagement leadership, acting as the bridge between customers, Sales, Pre-Sales, Delivery, Engineering, and Leadership.
You will ensure that every engagement is aligned with customer goals, successfully delivered, and positioned for long-term growth. You will proactively identify and remove blockers for both customers and delivery teams, drive clear communication and accountability, and ensure that issues are resolved quickly by the right stakeholders.
You will own the end-to-end customer journey, from the Sales-to-Delivery handover and project onboarding through delivery, UAT, adoption, renewals, and account expansion.
Why You? Why Now?
As enterprises rapidly adopt AI, customers need more than technology—they need a trusted partner who can understand their goals, align multiple stakeholders, anticipate risks, and ensure that AI solutions deliver measurable business value.
This role is ideal for someone who enjoys managing complex customer relationships, coordinating cross-functional teams, solving business and delivery challenges, and identifying opportunities to grow strategic accounts. You should also be curious about technology and interested in understanding how the right combination of technologies can solve customer problems.
You will ensure that customers are equipped with the information, guidance, and support they need to succeed, while enabling delivery teams with the clarity, context, access, and resources required to execute effectively.
What You’ll Do
First 30 Days: Foundation, Context & Account Understanding
- Build a strong understanding of GoML’s Generative AI, LLM, Agentic AI, AI/ML, and Data Engineering offerings, customer base, engagement model, and delivery processes.
- Understand existing customer accounts, active projects, signed Statements of Work, delivery workflows, and internal processes.
- Learn how Sales, Pre-Sales, Delivery, Engineering, and Leadership collaborate across ongoing and upcoming customer engagements.
- Review account plans, customer goals, business use cases, project milestones, stakeholder maps, renewal timelines, account health, risks, and expansion opportunities.
- Familiarize yourself with customer technical environments, infrastructure, data requirements, access dependencies, security considerations, and internal support structures.
- Build strong relationships with internal stakeholders and understand GoML’s customer communication, escalation, documentation, and engagement standards.
- Understand the expectations of acting as the bridge between customers and internal teams throughout the customer lifecycle.
- Review existing customer engagement cadences, project updates, risks, UAT plans, adoption status, and customer feedback.
- Serve as the primary point of contact for your customer accounts and own customer communication, stakeholder engagement, and relationship management.
- Establish and maintain an agreed customer engagement cadence through regular check-ins, project status meetings, stakeholder updates, and business reviews.
- Build trusted relationships with customer stakeholders across business, technical, operations, and leadership teams.
- Participate in Sales-to-Delivery handovers and ensure a smooth transition to project execution.
- Review signed Statements of Work and ensure that the solution being delivered remains aligned with the agreed scope, outcomes, and customer expectations.
- Reconfirm project scope, expected outcomes, dependencies, timelines, communication preferences, success criteria, and stakeholder responsibilities with the customer.
- Confirm business, data, technical, infrastructure, security, DevOps, access, and support-related prerequisites before project execution begins.
- Assess the customer’s technical readiness, including the availability of internal DevOps, infrastructure, security, data, and technical support teams.
- Identify readiness gaps and determine whether additional support from GoML is required before or during execution.
- Partner closely with Delivery and Engineering teams to track project progress, resolve blockers, and ensure that customer commitments are met.
- Identify customer concerns, delivery risks, dependencies, and scope gaps early, and coordinate resolution before they become escalations.
- Support realistic UAT planning by identifying customer-side UAT owners, testing expectations, timelines, sign-off processes, and required delivery support.
- Maintain accurate account documentation, stakeholder maps, engagement plans, project updates, risks, and mitigation plans.
- Track account health, customer satisfaction, adoption, escalations, project risks, renewal timelines, and potential growth opportunities.
- Communicate account insights, customer concerns, delivery challenges, and opportunities clearly to relevant internal stakeholders.
- Own a portfolio of strategic customer accounts and drive customer satisfaction, retention, adoption, renewals, and long-term expansion.
- Act as the customer champion internally and ensure that customer goals, expectations, priorities, and concerns are clearly understood across all relevant teams.
- Maintain living account plans covering customer goals, use cases, stakeholders, active projects, risks, dependencies, adoption, renewals, commercial milestones, and growth opportunities.
- Ensure continued alignment between signed scope, solution delivery, customer expectations, and measurable business outcomes.
- Identify early warning signs of customer dissatisfaction, delivery risk, project delays, adoption challenges, or potential churn, and coordinate mitigation plans.
- Build multi-threaded relationships across customer organizations to strengthen engagement and reduce dependency on individual stakeholders.
- Conduct structured customer reviews and business reviews to assess project performance, adoption, satisfaction, risks, value realization, and future priorities.
- Help customers successfully adopt, operationalize, and scale AI, ML, Generative AI, and Data Engineering solutions.
- Support post-deployment engagement and ensure that delivered solutions continue to provide measurable business value.
- Monitor UAT completion, customer sign-offs, deployment readiness, adoption progress, and post-production support requirements.
- Identify new use cases, additional business challenges, and account expansion opportunities.
- Coordinate with Sales and Pre-Sales teams to qualify and take forward new use cases, expansion opportunities, and commercial conversations.
- Partner with Sales on new-customer handovers, renewals, account expansion, and long-term account strategy.
- Work closely with Engineering, Delivery, and Leadership to provide structured customer feedback and influence solution and roadmap priorities.
- Develop repeatable practices for customer engagement, Sales-to-Delivery handovers, project readiness, UAT, risk management, adoption, account reviews, and customer success.
- Continuously improve customer experience, delivery alignment, internal coordination, retention, and account growth across the portfolio.
Must-Have
- 3–6 years of experience in customer-facing roles such as Account Management, Customer Success, Business Analyst, Engagement Management, Client Services, Program Management, or Project Management.
- Experience managing multiple customer accounts, customer projects, or strategic engagements.
- Strong experience working with cross-functional teams such as Sales, Pre-Sales, Delivery, Engineering, Product, and Leadership.
- Ability to understand customer business and technical requirements and translate them into clear execution plans.
- Experience reviewing project scope, deliverables, timelines, dependencies, risks, or Statements of Work.
- Strong communication skills with the ability to engage business, technical, operational, procurement, and executive stakeholders.
- Experience managing customer expectations, project risks, escalations, account health, satisfaction, renewals, or expansion opportunities.
- Strong stakeholder management, relationship-building, problem-solving, and conflict-resolution skills.
- Ability to balance customer expectations with delivery capacity, project scope, and internal priorities.
- Strong ownership and the ability to independently drive actions, follow-ups, and outcomes.
- Ability to manage ambiguity, prioritize effectively, and operate in a fast-paced environment.
- Excellent verbal, written, presentation, and documentation skills.
- Experience working with SaaS, technology services, AI, ML, Generative AI, Data Engineering, analytics, cloud, or operations-heavy businesses.
- Experience managing enterprise or mid-market customers.
- Experience working on technology implementation, consulting, managed services, or project-based customer engagements.
- Familiarity with CRM platforms, customer success tools, project management platforms, or delivery tracking systems.
- Exposure to solution scoping, proposals, pricing inputs, commercial discussions, renewals, or contract expansion.
- Experience conducting business reviews, preparing account plans, managing stakeholder maps, and presenting account insights.
- Familiarity with UAT planning, technical dependencies, infrastructure readiness, DevOps requirements, or deployment processes.
- Experience working with remote, global, or distributed teams and customers.
- Bachelor’s or Master’s degree in Business, Engineering, Computer Science, Management, or a related field.
- Strong business acumen and the ability to understand both commercial and technical conversations.
- High ownership, decisiveness, and comfort working in rapidly changing environments.
- Ability to structure complex information and communicate it clearly to customers and internal teams.
- Genuine interest in AI, ML, Generative AI, Data Engineering, and enterprise technology solutions.