AI Solutions Engineer – Salesforce Agentforce

Job description

**Keyloop bridges the gap between dealers, manufacturers, technology suppliers and car buyers.** We empower car dealers and manufacturers to fully embrace digital transformation. How? By creating innovative technology that makes selling cars better for our customers, and buying and owning cars better for theirs. We use cutting-edge technology to link our clients’ systems, departments and sites. We provide an open technology platform that’s shaping the industry for the future. We use data to help clients become more efficient, increase profitability and give more customers an amazing experience. **Want to be part of it?** This is a high-impact, highly collaborative role sitting at the intersection of AI engineering and customer service excellence. As an Agentforce Solutions Developer within the Customer Enablement (CE) organisation, you will be central to realising Keyloop’s investment in AI-powered customer operations – building, optimising and scaling intelligent agents to drive meaningful efficiency across our global support and service operations. You will work closely with CE leaders, functional heads, and cross-functional stakeholders to design and deliver a cohesive programme of AI-powered developments that reduce effort, accelerate resolution, improve customer outcomes, and advance the sophistication and autonomy of our AI agents. This role is part of Keyloop’s growing Global Delivery Hub in Vietnam. ### KEY RESPONSIBILITIES **Agentforce Platform Development** - Design, build and continuously improve AI agent flows within Salesforce Agentforce, progressing Kara’s capabilities across increasingly autonomous use cases - Develop and refine prompts, actions, flows, and integrations that enable Kara to handle increasingly complex support interactions autonomously - Maintain and extend the Agentforce knowledge base, working alongside the Knowledge & Education team to ensure high-quality, KCS-aligned content underpins AI responses - Integrate Agentforce with Keyloop's broader technology stack including Salesforce Service Cloud, internal DMS data, and the Fusion platform - Evaluate and integrate external LLM capabilities (e.g. Anthropic Claude API, Microsoft Copilot Studio) where they augment or extend Agentforce’s native functionality **Service & Process Efficiency** - Identify automation opportunities across CE processes – from first-contact resolution and case routing to proactive customer communication and self-service deflection - Partner with the Data Analytics team to analyse support data, case trends, and agent handling patterns to surface AI use cases that reduce manual effort and improve customer retention - Partner with the business to deploy solutions that directly reduce cost-to-serve while lifting customer satisfaction - Support the evolution of AI-assisted tooling for CE agents, including in-call guidance, auto-summarisation, and next-best-action recommendations **Cross-Functional Collaboration** - Engage CE leadership and heads of function (Support, Retention, Operations, Knowledge & Education) to align AI development priorities with strategic goals - Liaise with Keyloop's wider Product, Engineering, and AI CoE teams to ensure CE developments are coherent with platform-wide AI strategy - Communicate technical roadmaps, build progress and outcomes clearly to non-technical stakeholders, translating AI capability into business value **Quality, Governance & Continuous Improvement** - Apply rigorous testing, monitoring and feedback loops to ensure AI agents perform accurately, safely, and consistently at scale - Document technical designs, integration specifications, and operational runbooks to support team scalability and knowledge transfer - Stay current with Salesforce Agentforce releases, Einstein AI updates, LLM provider developments (Claude, Copilot), and emerging AI/ML trends relevant to customer service - Champion responsible AI principles in all development work, ensuring outputs are explainable, auditable, and aligned with Keyloop's values ### WHAT WE'RE LOOKING FOR **Essential** - Hands-on experience with Salesforce platform development – including Flows, Apex, and Lightning Web Components - Practical experience with Salesforce Agentforce, Einstein AI, or comparable conversational/generative AI development platforms - Strong understanding of API integration patterns and the ability to connect AI agents to third-party systems and data sources - Experience working with LLM APIs and orchestration (e.g. Anthropic Claude API, Azure OpenAI / Microsoft Copilot Studio) or a strong willingness to develop this expertise quickly - Understanding of prompt engineering principles, including techniques for grounding, guardrails, and output quality - Demonstrated ability to translate business requirements from non-technical stakeholders into working technical solutions - Experience working in customer service, support, or ITSM environments – understanding the workflow context your solutions will operate in - Clear and confident communicator in English, able to collaborate effectively across time zones and cultures **Desirable** - Experience with RAG (Retrieval-Augmented Generation) patterns or knowledge-grounded AI architectures - Familiarity with multi-agent or multi-model architectures – orchestrating workflows across different AI providers - Experience with JavaScript (relevant to Lightning Web Components and integration scripting) - Understanding of data privacy and AI governance considerations, particularly in multi-region operations - Interest in or exposure to automotive, DMS, or SaaS B2B software environments - Experience within a global delivery model, ideally collaborating with teams in the UK or Europe Salesforce certifications (e.g. Platform Developer I/II, Agentforce Specialist, Service Cloud Consultant) ### WHAT SUCCESS LOOKS LIKE In your first 90 days, you will have: - Developed a deep understanding of the CE function, its strategic goals, and the current Agentforce/Kara deployment - Identified and scoped your first high-value automation or AI improvement, with a clear delivery plan agreed with CE leadership - Established strong working relationships with your key stakeholders across CE and the wider Keyloop AI community Ongoing measures of success include: - Demonstrable progression of Kara’s agent capabilities across key CE use cases - Measurable reduction in manual handling time, case volumes, or cost-to-serve attributable to AI deployments - High adoption of AI tools by CE agents and positive feedback from both agents and customers On-time, high-quality delivery of agreed development work with clear documentation