Technical Account Manager

QuilrAI

About The Position

The Technical Account Manager (TAM) owns end-to-end technical delivery, product deployment, integrations, troubleshooting, and customer relationships. The role acts as a trusted technical advisor, supporting product adoption, smooth implementation, and effective customer support. It also focuses on customer success, product value, account growth, and enabling AI-driven transformation to improve business outcomes, increase AI adoption, and unlock opportunities for AUM growth. The posting also includes a separate Account Executive (Enterprise) description for WhiteMatter (Quilr). That role owns a named US territory and the full enterprise sales cycle, helping build the foundational AE team. It partners with the Chief Revenue Officer, sales engineering, and founders to shape enterprise messaging, sales playbooks, and go-to-market motions.

Requirements

3–6 years of experience in Technical Account Management, Technical Support, Product Implementation, or Customer Success roles; the posting does not specify the unit for this figure.
Hands-on experience in software deployment, product configuration, troubleshooting, and system integrations.
Working knowledge of sensors, APIs, hardware, and software integrations.
Experience managing technical projects and coordinating with cross-functional teams.
Strong customer relationship management, communication, and stakeholder engagement skills.
Ability to translate complex technical concepts into clear business solutions and communicate with senior stakeholders.
Strong analytical, problem-solving, documentation, and reporting skills.
Basic understanding of AI, automation, and digital transformation technologies.
Commercial acumen and ability to identify customer needs, upselling opportunities, and account growth potential.
Candidates must possess active, valid US work authorization; Quilr is currently unable to provide visa sponsorship.

Nice To Haves

Experience working with SaaS platforms, enterprise software, and financial services or wealth management solutions.
Familiarity with cloud technologies, APIs, IoT devices, sensor-based solutions, and third-party integrations.
Exposure to AI/ML solutions, automation tools, and implementing AI-driven business use cases.
Experience managing enterprise customer accounts, driving product adoption, demonstrating ROI, and identifying upselling or business expansion opportunities.

Responsibilities

Own end-to-end product deployment, including setup, configuration, fine-tuning, testing, and go-live.
Drive sensor and hardware rollouts, including integrations with customer systems and third-party applications.
Ensure successful deployment and operational readiness of the product.
Coordinate with internal product and engineering teams to resolve implementation challenges.
Own technical relationships with assigned customers and act as a trusted technical advisor.
Understand customer requirements, provide technical guidance, and conduct regular customer reviews.
Answer technical questions and independently troubleshoot product, configuration, and integration issues using established SOPs, targeting approximately 20% independent resolution of applicable issues.
Manage technical escalations, document issues, and recommend preventive solutions to recurring problems.
Manage customer implementation projects, including planning, milestones, timelines, and deliverables.
Coordinate customer and internal stakeholders to ensure successful and timely project execution.
Help customers measure and report outcomes, customer success, governance progress, ROI, and value realization.
Track product adoption, utilization, and business impact, and prepare executive-level reports and presentations.
Identify opportunities to increase product adoption and expand existing customer accounts.
Identify upselling and cross-selling opportunities across products, modules, sensors, and integrations.
Understand evolving customer requirements and recommend relevant solutions.
Collaborate with sales and account management teams to convert opportunities into account growth.
Understand customer business processes and identify opportunities for AI-driven transformation.
Recommend AI use cases to improve productivity, automation, operational efficiency, and decision-making.
Drive increased AI adoption across customer teams and business functions.
Identify opportunities where AI can unlock business value, increase AUM, improve portfolio performance, and support business growth.