ApplySarthi

Forward Deployed Engineer, AI & Agentforce

Jobgether

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What agentforce roles keep asking for: Salesforce (94%), CRM (79%), Customer success (75%), AWS (27%), B2B (27%), LLMs (26%), SaaS (23%), Generative AI (22%) — counted across their open postings here.

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Interviews for agentforce roles keep coming back to Salesforce, CRM, Customer success, AWS. Practise those questions before you sit with Jobgether.

Questions you are likely to be asked

  1. Why do you want to join Jobgether?
  2. What is your experience with Salesforce? Tell me one thing you learned the hard way.
  3. How did you know your model was actually good, and not just good on your test set?
  4. Tell me about a time the data was messy or wrong. What did you do?
  5. How would you explain your model's result to someone who is not technical?

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Accountabilities:: AI Solution Design and Development: Rapidly design and build AI-powered agents within client environments, translating business requirements into functional architectures that include subagents, deterministic guardrails, dynamic actions, and foundational data models. Rapid Prototyping and Proof of Value: Develop functional prototypes that validate technical feasibility, demonstrate business value, and help clients assess AI solutions before committing to broader implementations. Competitive Evaluations: Build and refine agentic AI solutions during competitive evaluations, incorporating client feedback in real time and demonstrating the capabilities of AI-driven architectures against alternative approaches. Client Engagement and Technical Leadership: Lead recurring technical sessions with clients, serve as the primary technical point of contact, demonstrate progress, gather feedback, clarify scope, and guide solution iterations throughout the engagement. Business Value Demonstration: Connect technical capabilities to measurable business outcomes, including customer service deflection, reduced handling times, lower operating costs, and improved user satisfaction. Present findings clearly to executives and non-technical stakeholders. Live Demonstrations: Design and deliver interactive demonstrations that showcase advanced AI agent capabilities, handle technical questions, and communicate the practical value of proposed solutions. Technical Troubleshooting and Optimization: Diagnose and resolve issues involving dialogue flows, agent execution, integrations, system logic, and platform constraints. Optimize solutions under tight deadlines while maintaining functionality and reliability. Architecture and Integration: Assess enterprise architecture requirements, integration dependencies, data models, and platform limitations to ensure proposed solutions are technically feasible and aligned with client environments. Risk Identification and Delivery Management: Identify delivery bottlenecks, integration challenges, architectural limitations, and stakeholder misalignment early. Communicate risks proactively and implement solutions that maintain momentum against demanding milestones. Reusable Assets and Knowledge Sharing: Convert lessons learned from client engagements into reusable solution accelerators, demonstration assets, technical documentation, and internal knowledge resources that improve future delivery efficiency. AI-Driven Productivity: Use modern AI development tools and emerging technologies to accelerate prototyping, improve execution speed, and increase the effectiveness of technical delivery. Requirements: Professional Experience: At least 4 years of experience delivering technical solutions, consulting, or solution engineering in client-facing environments, including direct engagement with key stakeholders during important business or technical decisions. Hands-On AI and Platform Experience: At least 2 years of practical experience building solutions with Agentforce, Service Cloud, or comparable agentic AI architectures. Candidates should have experience implementing and architecting functional solutions rather than focusing exclusively on theoretical designs. Salesforce Certifications: Active Salesforce credentials, including Agentforce Specialist, Platform Developer I, or System Administrator certification. Rapid Prototyping and Debugging: Demonstrated ability to build functional solutions quickly, troubleshoot technical issues in real time, and analyze Salesforce Flows, Apex code, or agent execution traces to identify root causes and implement fixes under pressure. Enterprise Architecture Knowledge: Strong understanding of enterprise architecture principles, integration patterns, data modeling, and platform boundaries, with the ability to distinguish technical possibilities from limitations and make sound architectural decisions. Business and Technical Communication: Ability to translate complex technical concepts and trade-offs into clear business outcomes, address stakeholder concerns, and explain how proposed solutions support operational and strategic objectives. Client-Facing Collaboration: Strong communication, presentation, and stakeholder management skills, with the confidence to lead technical discussions, deliver live demonstrations, and adapt solutions based on client feedback. Analytical Problem-Solving: Excellent troubleshooting, critical-thinking, and decision-making skills, combined with the ability to navigate ambiguity and resolve complex problems within compressed delivery timelines. AI Tool Proficiency: A strong commitment to using modern AI tools to improve productivity and accelerate development. Familiarity with AI-assisted platforms such as Claude is particularly valuable. Adaptability and Ownership: Comfort working in fast-moving environments where priorities evolve quickly, requirements may be ambiguous, and engineers are expected to take ownership and help define the best path forward. Preferred Qualifications: Experience leading competitive technology evaluations, rapid proof-of-value engagements, pre-sales demonstrations, or AI-focused consulting projects. Expertise in telephony and voice integration platforms, such as Service Cloud Voice, Amazon Connect, Genesys, or NICE. Familiarity with broader agentic AI ecosystems, including Amazon Bedrock, Google Vertex AI, and modern large language model orchestration frameworks. Experience with enterprise data platforms and architectures, including Salesforce Data 360, Snowflake, Databricks, or BigQuery. Ability to balance technical depth with commercial awareness, helping clients understand both the possibilities and practical limitations of emerging AI technologies. Benefits: Remote work flexibility: Work remotely from eligible locations in Canada, specifically Alberta, British Columbia, or Ontario. Flexible working arrangements: A trust-based culture that prioritizes results and high-quality work over rigid working hours, supporting personal and professional commitments. Meaningful AI innovation: Work with advanced generative AI, autonomous agents, and enterprise technologies to solve complex business challenges and deliver measurable customer value. Professional growth: Gain exposure to emerging AI architectures, Salesforce technologies, enterprise integrations, and client-facing technical leadership. Collaborative environment: Work alongside experienced technical specialists, architects, and business leaders in a culture that encourages feedback, knowledge sharing, and continuous improvement. Employee engagement: Participate in team celebrations, company meetings, leadership town halls, and collaborative initiatives that encourage connection and recognize achievements. Travel opportunities: Some client-facing activities may involve travel, with an anticipated commitment of up to 25%, depending on business needs and the role's requirements.

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Listed on lever · posted 2026-10-16. ApplySarthi collects openings and links to application pages; the role is advertised by Jobgether, not by us.