Sales & GTM
Finding, winning, and growing customer relationships. Covers sales (AE, SDR/BDR), enterprise/strategic sales, business development, partnerships, channel sales, revenue operations, solutions architecture, solutions engineering, technical pre-sales and post-sales support, deal desk, sales enablement, and business value consulting.
Roles
The canonical roles within Sales & GTM.
Account Executive
Account Executives at AI companies own named customer relationships and drive revenue across the full sales cycle—prospecting, discovery, negotiation, renewal, and expansion. The day-to-day is classical enterprise sales: running discovery against multi-stakeholder buying committees, building executive relationships, navigating procurement and security reviews, and managing pipeline against quota. What distinguishes selling at AI companies is not a different sales motion—buyers still evaluate against business outcomes—but the category being sold and the pace at which product capabilities evolve, requiring working fluency in the product without owning the technical evaluation. These roles sit within enterprise or mid-market sales teams, partnering with solutions engineers on technical work and customer success on post-sale adoption.
Solutions Architect
Solutions Architects combine deep technical expertise with customer-facing acumen to guide enterprise clients through complex adoption decisions. They own end-to-end account strategy, from initial discovery and architecture design through proof-of-concept execution and production deployment, becoming trusted advisors on how AI and data platforms solve specific business problems. Operating at the intersection of sales and engineering, these roles work closely with account executives, product teams, and customer technical leads to design differentiated solutions, lead competitive technical wins, and ultimately drive adoption and revenue expansion. They typically specialize in emerging domains—whether distributed systems, real-time analytics, AI/ML, or cloud infrastructure—and serve as go-to resources within their teams, while feeding structured feedback back to product on customer needs and market gaps.
Solutions Engineer
Solutions Engineers serve as technical bridges between sales and customers, designing and building proof-of-concept integrations while demonstrating how AI and data platforms solve complex business problems. They excel at translating customer requirements into technical architectures, running hands-on evaluations and live demos, and providing white-glove support through implementation. Unlike Solutions Architects who focus on long-term strategic design, these engineers are more involved in day-to-day problem-solving and rapid prototyping. They typically sit within GTM-aligned teams, partnering closely with Account Executives and Sales to accelerate deal cycles while gathering market feedback that informs product strategy.
Sales Leadership
Sales leaders in this role build and mentor teams of Account Executives selling data infrastructure, AI platforms, or security solutions to mid-market and enterprise customers. They balance hands-on coaching—joining calls, refining messaging, and managing deals—with strategic responsibilities like territory planning, quota setting, and pipeline forecasting. These leaders operate at the intersection of revenue accountability and people development, creating scalable sales processes while cultivating a high-performance culture that attracts and develops top talent.
Partner & Channel Manager
Partner & Channel Managers at AI companies own partner relationships across the partnership lifecycle—from sourcing and structuring new agreements through enablement, joint go-to-market execution, and revenue tracking. The role spans both relationship development and operational delivery: identifying and qualifying potential partners, negotiating commercial terms, building enablement materials and joint sales motions, and managing the cadence of business reviews and pipeline tracking against partner-sourced revenue targets. Specific partnership types vary—technology partners for joint solutions, channel resellers for indirect revenue, system integrators for delivery capacity—and most managers cover more than one. These roles typically sit within partnerships, business development, or alliance functions, partnering closely with sales, product marketing, solutions engineering, and product on what the partner relationship needs to deliver.
Sales Development Representative
Sales Development Representatives at AI companies generate and qualify pipeline through inbound and outbound prospecting—working leads from marketing, conducting outreach against target account lists, running discovery calls, and converting qualified prospects into meetings for account executives. The day-to-day is classical SDR work: hitting daily activity targets across email, phone, and social, researching accounts and personalizing outreach, qualifying against ideal-customer-profile criteria, and maintaining CRM hygiene through the funnel. SDRs at AI companies need working fluency in their company's product to talk credibly with prospects, but the depth of technical knowledge required is no different from the SDR role at any high-growth software business. These roles typically sit within centralized SDR teams reporting to sales development leadership, partnering with marketing, account executives, and sales operations on conversion and pipeline health.
Client Partner
Client Partners at AI companies serve as strategic relationship managers for a focused portfolio of high-value accounts, combining deep technical fluency with executive presence to guide customers through complex AI adoption journeys. Day-to-day, they develop comprehensive account strategies, lead customers from discovery through successful deployment, partner with engineering and product teams to solve mission-critical problems, and own revenue targets while monitoring industry landscapes to inform company strategy. What distinguishes this role from other enterprise sales positions is its emphasis on being a trusted advisor who helps customers understand transformative AI capabilities specific to their industry or use case, rather than simply closing transactions. These roles typically sit within specialized go-to-market teams—whether focused on government, startups, enterprises, or strategic verticals—working closely with solutions architects, research engineers, and cross-functional leadership to ensure customers realize measurable business value from AI-powered solutions.
Field Engineering Management
This role leads teams of solutions architects and engineers who guide enterprise customers from initial AI discovery through production deployment. The manager sets technical strategy, owns customer technical outcomes, and serves as both a people leader and senior technical advisor—coaching engineers through architecture decisions, managing resource allocation across accounts, and escalating on complex implementations. What distinguishes this from pure sales engineering is the emphasis on post-sales technical strategy, production value realization, and building repeatable implementation patterns that scale across a customer portfolio. These leaders typically sit in go-to-market organizations alongside Sales and Customer Success, translating customer business objectives into credible technical roadmaps while developing their team's expertise in platform architecture, deployment patterns, and adoption methodologies.
Revenue & Sales Operations
This role owns the operational heartbeat of sales organizations in AI companies, managing forecasting, pipeline hygiene, territory strategy, and sales process architecture across pre-sales functions like Sales Development and Sales Engineering. Unlike pure analytics or enablement roles, Revenue & Sales Operations leaders drive execution rigor through systems and methodology—they design the processes sellers actually follow, diagnose why pipelines stall, and build the metrics that predict revenue before quarter-end. These operators typically sit within larger GTM organizations, partnering closely with Sales leadership, Finance, and RevOps teams to translate growth targets into repeatable sales motions that scale as the company grows and AI capabilities evolve.
Applied AI Architect
Applied AI Architects serve as the senior technical owner for a customer portfolio, acting as the "CTO of their book of business" and guiding organizations from pre-sales discovery through deployment and adoption of LLM-powered solutions. They translate business or mission priorities into focused use-case portfolios and actionable adoption roadmaps, balancing hands-on prototyping and architecture design with executive-level strategy conversations. What sets this role apart is its accountability for both technical outcomes and customer success across a named set of accounts, sitting in the GTM organization rather than the product team, and the ability to orchestrate specialists across deployment, enablement, security, and product while maintaining the primary technical relationship with leadership.
Deployment Strategist
Deployment Strategists embed themselves inside enterprise customers to drive AI adoption end-to-end, translating complex business problems into scoped implementations and owning outcomes rather than code. Day-to-day, they conduct discovery across customer workflows, architect bespoke solutions with technical teams, guide configuration decisions, and manage multi-stakeholder projects from sales handoff through production launch. Unlike account executives or implementation managers, they blend product thinking with field execution—writing requirements, managing scope ruthlessly, and acting as trusted technical advisors who can speak both to C-suite strategy and engineering constraints. These generalists typically sit within customer success, deployment, or forward-deployed engineering functions at AI platforms, working closely with both customers and internal engineers to prove out impact at each account.
GTM Enablement Manager
This role designs and delivers scalable enablement programs that accelerate how field teams—sellers, solutions engineers, and customer-facing staff—ramp and execute with confidence. It spans onboarding, product training, and ongoing skill development, with particular emphasis on embedding AI-native workflows and agentic tools that fundamentally change what teams can accomplish. The GTM Enablement Manager typically sits in a dedicated enablement function or within revenue operations, working cross-functionally with sales leadership, product, and marketing to ensure programs are grounded in real performance data and measurable outcomes. What distinguishes this role is its focus on building repeatable systems that scale beyond the enablement leader themselves—from reinforcement cadences embedded in manager coaching to AI-powered delivery mechanisms—rather than delivering training on demand.
Product Specialist
Product Specialists at AI companies bring deep product and domain expertise into enterprise sales cycles, supporting account executives on complex deals where the buyer needs more depth than a generalist seller can provide. In practice, this slug skews toward regulated-industry sales—financial services, healthcare, government, life sciences—where the specialist's edge comes from fluency in regulatory frameworks and compliance requirements as much as from product depth. The day-to-day involves leading discovery and proof-of-value engagements, articulating differentiated value propositions to mixed technical-and-business audiences, and helping account teams navigate the longer evaluation cycles typical of regulated buyers. These roles typically sit within enterprise sales or field engineering organizations, partnering with account executives, solutions architects, and product on the most complex opportunities in the pipeline.
GTM Engineer
GTM Engineers solve revenue operations problems by building, not buying: they architect CRM data models and integration layers, orchestrate AI agents that automate sales workflows from enrichment through pipeline management, and instrument everything with observability so systems improve continuously rather than degrade. They sit at the intersection of technical depth and commercial judgment, treating the go-to-market function as a product that serves both field teams and the business, designing systems that scale productivity-per-FTE as the organization grows. This role typically reports into Revenue Operations or GTM leadership and works cross-functionally with sales, marketing, and product teams, often managing small technical teams while staying hands-on with the hardest technical problems and highest-leverage initiatives.
Proposal & Capture Manager
Proposal and Capture Managers lead the end-to-end lifecycle of federal and international government opportunities for AI defense companies, managing competitive intelligence, customer engagement with defense and intelligence agencies, and proposal strategy from early qualification through award. They distinguish themselves from quota-carrying Account Executives by focusing on pursuit operations, capture planning, and bid execution rather than direct revenue targets, and from internal Program Managers by owning the external business development process. These roles typically sit within dedicated Business Development Operations or Capture teams, coordinating cross-functionally across sales, engineering, legal, and security to navigate complex procurement vehicles like GSA schedules, IDIQs, and OTAs while building institutional knowledge that compounds across multiple pursuits.
Business Value Consultant
This role guides enterprise customers through AI adoption by building financial models and business cases that quantify the impact of AI solutions on cost reduction, revenue growth, and operational efficiency. Business Value Consultants work across the entire customer lifecycle—from pre-sales discovery through post-implementation value realization—translating complex technical capabilities into executive-ready narratives that drive deal velocity and expansion. They distinguish themselves by combining deep financial acumen with customer strategy expertise, operating as trusted advisors rather than transactional sellers. Typically embedded within GTM teams alongside Sales and Success, they develop scalable frameworks and benchmarks that enable broader field teams to sell and measure value consistently.
Recent Jobs
The latest Sales & GTM openings across the AI industry.