Assistant Vice President- Digital Sales – Agentic AP Solution

Genpact
London
2 months ago
Applications closed

Related Jobs

View all jobs

Assistant Professor in Data Science

Accounts Assistant

Software Engineer (Machine Learning)

Data Analyst

Research Fellow in Spatial Data Science (Public Health)

Data & Analytics Engineer

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertisein data, technology, and AI.

Inviting applications for the role of Assistant Vice President- Digital Sales – Agentic AP Solution

The Digital Sales individual will be a member of a dynamic team driving growth of digital solutions in a prioritized portfolio of existing and new accounts. Creating, shaping, and responding to the ever-increasing new challenges being faced within one of the specific industry verticals such as Consumer goods, Retail, Hi Tech and Manufacturing, Banking & financial services, in support of Genpact’s Sales and Transformation Services community.

The digital sales team has recently enjoyed good growth and made notable wins with new logos, as well as increasing the digital footprint with existing customers. This role will identify, shape and close revenue generating opportunities in new and existing accounts on a foundation of carefully selected & curated, repeatable offerings and solutions for driving change in specific vertical industries. The role will combine leading edge digital solutions with your deep domain expertise to create innovation and thought leadership opportunities!

Responsibilities

Display strong domain knowledge in Finance and Accounting processes with demonstrated ability to drive business solutions in Accounts Payable, Record to Report etc

Identify and target potential clients through various channels such as networking and social media.

Drive Software sales in Retail environment with clients where Genpact doesn’t perform managed services.

Demonstrate an understanding of a client’s business and use of Digital technologies to craft transformational value propositions for the clients.

Proactively create, identify, and develop opportunities for our proprietary Agentic SaaS solution in the Finance & Accounting domain

Demonstrate understanding of Artificial Intelligence (AI) technologies like Generative AI, Machine Learning, Large Language Models etc

Provide domain and digital solution expertise and support to internal teams including participation in RFI, RFP, proactive bids, customer-facing envisioning sessions/demonstrations, assessments, and workshops.

Own delivery estimations, solutioning and pricing for proposed client solutions and working closely with Genpact and client is legal in the creation and review of customer commercial agreements, License / SaaS, SOW, Change requests etc.

This role reports to the Global Agentic Growth Leader & Growth Leader for Digital. The Senior Digital Advisor / Seller will work in close partnership with Genpact Sales, Solutions, SMEs, Partner (Microsoft) Account teams and other consulting leaders within Genpact in successfully establishing and growing client relationships, innovating with clients and winning deals.

Qualifications we seek in you!

Minimum Qualifications / Skills

Product Knowledge: Deep understanding of finance and accounting solutions, including features, benefits, and how it meets the needs of different businesses.

Industry Expertise: Familiarity with the different industries including CPG, Hi Tech & Manufacturing

Sales Skills: Strong abilities in prospecting, qualifying leads, presenting solutions, negotiating, and closing deals

Proven Experience and success in driving SaaS product sales.

Communication Skills: Excellent verbal and written communication to effectively convey complex information and build relationships with clients.

Customer-Centric Approach: Focus on understanding and addressing the specific needs and pain points of customers.

Problem-Solving Skills: Aptitude for identifying customer problems and proposing tailored solutions.

Adaptability: Flexibility to adapt to different customer needs and market changes.

Persistence and Resilience: Determination to pursue leads and handle rejection positively.

Team Collaboration: Ability to work well with marketing, product development, and customer support teams to ensure customer satisfaction.

Preferred Qualifications/ Skills

Deep expertise in one or more specific industry verticals such as Manufacturing, High Tech Software, Hardware, Hospitality, Services, Logistics, Media, Telco, and/or Entertainment.

Good cultural fit – role model in (CI)2 i.e., curious, incisive, and courageous, on a bedrock of integrity.

Good “roll up the sleeves” collaboration attitude to work across Genpact, client teams and Genpact’s SaaS partners to bring the greatest possible impact through new ways of working.

Technical understanding of SaaS architecture, integrations, and domain expertise

Ability to engage, and work with C level executives on the client side.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.