AI Business Development Jobs

Discover the latest remote and onsite AI Business Development roles across top active AI companies. Updated hourly.

Check out 136 new AI Business Development opportunities posted on AI Chopping Block

AI Deployment Strategist, AI4Engineering - EMEA

New
Top rated
Mistral AI
Full-time
Full-time
Posted

As an AI Deployment Strategist, responsibilities include driving the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation. Leading executive-level workshops to identify business challenges and opportunities, co-creating AI adoption roadmaps with customers, and partnering with Account Executives to develop business cases. Architecting end-to-end AI solutions by integrating Mistral’s models and platform into customer workflows and technical infrastructure, collaborating with the Applied AI team to design, prototype, and deploy scalable AI solutions in production. Owning pilots and proofs-of-value, demonstrating technology potential and enabling full-scale deployments. Serving as a trusted advisor to guide customer AI strategy, monitoring outcome-driven KPIs, and identifying expansion opportunities within accounts. Acting as a liaison between customers and Mistral’s internal teams to influence product and research roadmaps, creating reusable assets and best practices to scale go-to-market efforts, and traveling 30–60% to support client relationships and on-site deployments. Additionally, translating industrial engineering challenges into AI use cases, designing hybrid AI-physics pipelines validated against ground truth simulations, navigating enterprise IT constraints including deployment in air-gapped environments or on-prem HPC clusters, and conducting hands-on workshops with engineers to upskill teams on AI-assisted workflows.

Undisclosed

()

Paris, France
Maybe global
Onsite

Generative AI Engineer

New
Top rated
Dataiku
Full-time
Full-time
Posted

The role involves supporting Dataiku’s strategic vision towards Healthcare & Life Sciences to accelerate growth in this industry by developing a deep understanding of Dataiku’s footprint and supporting plans to meet ambitions. Acting as a Dataiku subject matter expert (SME) on Healthcare & Life Sciences, the position requires bridging the gap between industry needs, AI, and Dataiku’s product, supporting clients and prospects as a trusted expert, and supporting development of assets and engagement support to enhance GTM effectiveness. Tasks include supporting sales and customer activities, articulating Dataiku's value proposal for Life Sciences, leveraging internal knowledge and client experiences, engaging in thought-leadership strategies, and driving high impact customer engagements. The role also entails identifying, scoping, and rolling out Dataiku Solutions aligned to Healthcare and Life Sciences needs to maximize value delivery. This includes fueling the solutions development pipeline through business experience, client workshops, market monitoring, partnership discussions, and partnering with the Solutions taskforce in ensuring prompt development of relevant projects like off-the-shelf designs, customer-specific solutions, and feature/application development. Supporting the general AI Solutions offering by contributing to documents, team enablement, customer interactions, and go-to-market materials is also required.

Undisclosed

()

New York, United States
Maybe global
Onsite

GTM Engineer - Seller Efficiency

New
Top rated
Clay
Full-time
Full-time
Posted

The GTM Engineer - Seller Efficiency is responsible for building and owning core sales workflow automations such as book carving, ROE automation, signal detection, and pipeline automation. They partner closely with the Head of Sales and sales leadership to translate business needs into automation requirements and iterate based on feedback. The role involves building tooling that provides the right customer context for GSMs at critical moments like QBRs, renewals, and expansion conversations. The engineer pushes the limits of Clay and extends the platform into new use cases, feeding product teams with innovative ideas and acting as a practitioner evangelist of Clay infrastructure and GTM Engineering. They partner deeply with GTM leaders and frontline teams to understand revenue motions and identify breakpoints. The engineer owns projects end-to-end from discovery and prototyping through rollout, adoption, and iteration, including automating, augmenting, or redesigning workflows using AI, data, and systems design. They design systems that improve speed, visibility, data quality, and execution across the funnel, connect systems through APIs, webhooks, integrations, and automation layers. They measure the performance, adoption, and business impact of built solutions and improve them over time. Additionally, they act as an internal thought partner on the future of AI-native GTM systems.

$140,000 – $180,000
Undisclosed
YEAR

(USD)

New York, United States
Maybe global
Remote

AI Strategist, Healthcare Solutions

New
Top rated
Distyl
Full-time
Full-time
Posted

As an AI Strategist in Healthcare, you will lead and drive technology solutions within the healthcare vertical and manage the go-to-market (GTM) process with healthcare client engagements from initial meetings through deal closure. Responsibilities include diagnosing client problems through an AI perspective, designing data-driven AI strategies to transform operations and improve outcomes, and rapidly building demos and proof-of-concept solutions on the Distillery platform to demonstrate capabilities to prospective healthcare clients. You will work at the intersection of business strategy and AI implementation by bridging the gap between technical AI tools and business outcomes, collaborating closely with healthcare subject matter experts, and taking ownership of the entire pre-sales process including discovery, solution architecture, and feasibility. Additional duties involve researching clients and their industry landscapes to tailor use case materials, feeding insights to account executives to refine pitches, co-designing solutions with engineering, navigating enterprise data constraints to produce reliable AI outcomes, creating compelling AI ROI storylines and decks, developing reusable GTM assets, maintaining pre-sales account documentation, and ensuring formal handoff to expansion teams.

$150,000 – $250,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Hybrid

Senior Manager, Revenue Operations

New
Top rated
Glean Work
Full-time
Full-time
Posted

The AI Outcomes Manager partners with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on the Glean platform. They lead strategic reviews and advise customers on their AI roadmap to maximize value, translate business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D. They conduct discovery workshops, scope pilots, guide rollouts to drive adoption of the Glean platform, design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability, and proactively identify expansion opportunities and drive engagement across teams and functions.

Undisclosed

()

Bangalore, India
Maybe global
Hybrid

Founder in Residence, Open Application for Founders

New
Top rated
Mistral AI
Full-time
Full-time
Posted

The role involves joining Mistral's Solutions team with the mission to take the company's AI models and make them indispensable for enterprise clients. Responsibilities include owning a portfolio of enterprise clients and acting as their primary point of contact and co-builder, identifying high-impact use cases, structuring deployments, and removing obstacles. The role requires bridging the gap between the AI models' capabilities and client needs, addressing issues ranging from prompting to executive-level challenges. Additionally, the person feeds back signals from the field to product and research teams. Depending on background, one may focus either on deployment strategy (including business cases, C-level adoption, executive workshops, adoption roadmaps, and ROI proposals) or on applied AI engineering (including integration architecture, fine-tuning, production deployment, prototypes, deployment pipelines, client code, and open-source contributions).

Undisclosed

()

Paris, France
Maybe global
Onsite

Senior Manager, Revenue Operations

New
Top rated
Glean Work
Full-time
Full-time
Posted

The AI Outcomes Manager at Glean partners with executive sponsors and end users to identify high-impact use cases and transform them into measurable business outcomes using the Glean platform. Responsibilities include leading strategic reviews, advising customers on their AI roadmap, translating business needs into clear problem statements and AI solutions, collaborating with Product and R&D teams, conducting discovery workshops, scoping pilots, guiding rollouts to drive adoption, designing and building AI agents with customers, redesigning business processes for impact and usability, and proactively identifying expansion opportunities to drive engagement across teams and functions.

Undisclosed

()

Bangalore or Nashville, United States or India
Maybe global
Hybrid

Deployment Strategist Lead - France

New
Top rated
ElevenLabs
Full-time
Full-time
Posted

As a Deployment Strategist Lead, you will be fully responsible for opening up a new market for ElevenLabs, building and leading a team to achieve this. Your duties include meeting with strategic customers to understand their critical audio and voice AI needs and pain points, building and leading a team of forward deployed engineers within the region, identifying relevant use cases by deeply engaging with customer problems and workflows, and working with engineers to implement voice and audio AI technology into innovative solutions. You will design and architect bespoke integrations for customers to ensure seamless technology fit, guide customers on best practices for implementing voice and audio AI models, present results and proposals to audiences ranging from technical teams to executives, collaborate with research and product teams to incorporate field insights into software products and AI models, build and deliver demos of voice and audio AI technology, scope potential applications in new industries, expand AI solutions globally, take full ownership of major projects for strategic partners and work hands-on to deliver high-impact solutions, and collaborate daily with customer engineering and executive teams to ensure optimal technology implementation.

Undisclosed

()

Paris, France
Maybe global
Hybrid

Senior Manager, Revenue Operations

New
Top rated
Glean Work
Full-time
Full-time
Posted

The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes using the Glean platform. They will lead strategic reviews and advise customers on their AI roadmap to maximize value from the platform. Responsibilities include translating business needs into clear problem statements, success metrics, and practical AI solutions, collaborating with Product and R&D to shape priorities. The role involves conducting discovery workshops, scoping pilots, guiding rollouts, and driving adoption breadth and depth of the Glean platform. Additionally, the manager will design and build AI agents with and for customers, rethink and redesign underlying business processes to maximize impact and usability, proactively identify expansion opportunities, and drive engagement across teams and functions.

Undisclosed

()

Bangalore or San Francisco, India or United States
Maybe global
Hybrid

Product Partnerships Lead, Ecosystem

New
Top rated
OpenAI
Full-time
Full-time
Posted

Lead the strategy and execution for OpenAI's app and connector ecosystem, building deep partnerships and managing the full partnership lifecycle from identification to negotiation and closing. Collaborate with internal teams and executive leadership to ensure successful partner integrations and advance innovation within the ecosystem.

Undisclosed
YEAR

(USD)

Maybe global
Hybrid

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[{"question":"What does an AI Business Development do?","answer":"AI Business Development professionals identify and pursue opportunities in AI-relevant sectors through market research, networking, and outreach. They build client relationships, understand business needs, and translate these into customized AI solutions. Their responsibilities include developing sales strategies, creating proposals, responding to RFPs, and collaborating with cross-functional teams on go-to-market approaches. They analyze market trends and AI technologies to inform strategies, track pipeline metrics using CRM systems, and represent their company at industry events. Many also mentor sales development representatives on lead generation techniques specific to AI solutions."},{"question":"What skills are required for AI Business Development Roles?","answer":"Successful AI Business Development professionals need a blend of technical and interpersonal abilities. Key skills include consultative selling, where understanding client challenges takes precedence over product pitching. Strong communication is essential for explaining complex AI concepts to non-technical stakeholders. Market analysis capabilities help identify trends and opportunities. Negotiation expertise facilitates deal closing, while relationship building creates long-term partnerships. Technical comprehension of machine learning, data analytics, and automation principles is crucial. Proficiency with CRM systems and sales automation tools streamlines processes. Strategic thinking allows for aligning AI solutions with client business objectives and measuring impact."},{"question":"What qualifications are needed for AI Business Development Roles?","answer":"Employers typically seek candidates with proven business development experience in technology sectors, particularly with AI, software, or SaaS products. A bachelor's degree in business, computer science, or related field is standard, with MBAs sometimes preferred for senior positions. Technical knowledge of AI concepts and applications must be sufficient to have meaningful conversations with both technical teams and business stakeholders. Demonstrated revenue generation and a track record of meeting sales targets are essential qualifications. Experience with CRM platforms, proposal development, and contract negotiations strengthen applications. Industry certifications in sales methodology or specific AI technologies can provide competitive advantages."},{"question":"What is the salary range for AI Business Development Jobs?","answer":"Compensation for AI Business Development roles varies based on several factors. Geographic location significantly impacts earnings, with technology hubs like San Francisco, New York, and Boston typically offering higher packages. Experience level creates substantial differences, with senior professionals commanding significantly more. Company size and funding stage affect compensation structures – established enterprises often provide higher base salaries while startups might offer more equity. Technical expertise depth can increase earning potential, particularly knowledge of specialized AI applications. Commission structures vary widely, with some roles offering substantial performance-based incentives. Education level and industry specialization (healthcare AI versus retail AI) also influence compensation packages."},{"question":"How long does it take to get hired as an AI Business Development?","answer":"The hiring timeline for AI Business Development positions typically spans 1-3 months. Initial screening often includes resume review and preliminary calls with recruiters or hiring managers. Technical screening may assess AI knowledge through scenarios or case studies. Multiple interview rounds follow, typically including conversations with sales leadership, product teams, and potential cross-functional partners. For senior roles, presentations demonstrating market understanding or sales approaches are common. Reference checks and background verification precede offer negotiation. The process may extend longer at larger organizations with formal hiring committees or when specialized industry expertise (healthcare, finance) is required. Candidate availability and scheduling can also impact timelines."},{"question":"Are AI Business Development Jobs in demand?","answer":"AI Business Development roles show strong demand signals across multiple sectors. Companies like ServiceNow, OpenAI, and numerous AI startups are actively recruiting for these positions. The integration of AI capabilities into traditional business solutions has created need for professionals who can articulate technical value propositions to non-technical buyers. Organizations seek specialists who understand both AI technology limitations and business applications. Demand is particularly high in industries undergoing AI transformation, including healthcare, financial services, retail, and logistics. The specialized knowledge required—combining sales expertise with AI understanding—has created a talent gap that companies are eager to fill with qualified professionals."},{"question":"What is the difference between AI Business Development and Traditional Business Development?","answer":"AI Business Development requires deeper technical knowledge to effectively communicate complex solutions to prospects. While traditional roles focus on general value propositions, AI specialists must translate technical capabilities into business outcomes and ROI frameworks. AI positions often involve longer sales cycles with more stakeholders, including data scientists and IT leaders. The demonstration process differs significantly—AI roles frequently require custom proof-of-concepts showing specific data applications rather than standard product demos. Technical qualification of opportunities becomes critical, assessing data readiness and integration requirements. AI professionals must stay current with rapidly evolving technologies and regulatory considerations like data privacy that may not impact traditional business development professionals."}]