Salesforce Application Manager

Join a Global Leader in Workforce Solutions - Net2Source Inc.

Who We Are

Net2Source Inc. isn't just another staffing company, we're a powerhouse of innovation, connecting top talent with the right opportunities. Recognized for 300% growth in the past three years, we operate in 34 countries with a global team of 5,500+. Our mission? To bridge the talent gap with precision-Right Talent. Right Time. Right Place. Right Price.

Description:

Role Name: Salesforce Application Manager

Location: Menlo Park, CA. ONSITE

Duration: 12+ Months

Job Description:

1. AI Evaluation Framework Development

• Design and implement a comprehensive evaluation framework for AI-generated employee support responses.
• Establish automated and human-in-the-loop evaluation workflows.
• Develop mechanisms to assess:
• Response accuracy
• Completeness
• Relevance
• Clarity
• Tone
• Groundedness
• Policy compliance
• Employee experience quality
• Build configurable evaluation scorecards and quality thresholds.
• Enable evaluation across multiple use cases, channels, employee groups, and support domains.
• Maintain versioned evaluation datasets, benchmarks, and test scenarios.

2. Salesforce Application Engineering

• Design, configure, and develop Salesforce solutions supporting AI quality assurance and evaluation.
• Build custom objects, Apex services, Lightning Web Components, flows, validation rules, and automation.
• Develop reusable services for capturing AI prompts, responses, source references, confidence scores, and evaluation outcomes.
• Extend Salesforce Service Cloud and related employee support capabilities.
• Implement secure, scalable, and maintainable solutions aligned with Salesforce engineering standards.
• Support sandbox, development, testing, staging, and production environments.

3. Response Quality Measurement

• Create automated evaluation pipelines for AI-generated and human-assisted responses.
• Compare responses against approved knowledge sources, expected answers, and business policies.
• Develop scoring logic for factual accuracy, relevance, completeness, and actionability.
• Capture evaluator feedback and convert it into structured quality metrics.
• Build workflows for sampling and reviewing high-risk or low-confidence interactions.
• Enable trend analysis by use case, model version, region, policy area, and interaction type.

4. Hallucination Detection and Grounding Validation

• Develop mechanisms to identify unsupported, fabricated, or inconsistent AI responses.
• Validate whether responses are grounded in approved enterprise knowledge sources.
• Capture and assess citations, source references, retrieval results, and confidence indicators.
• Flag responses that contain unverifiable claims or contradict enterprise policy.
• Route suspected hallucinations for human review and remediation.
• Partner with AI and data science teams to improve retrieval, prompting, and model behavior.

5. Regression Testing Infrastructure

• Build automated regression suites for AI-enabled Salesforce capabilities.
• Maintain benchmark prompts, expected responses, edge cases, and negative test scenarios.
• Compare response quality across model, prompt, knowledge base, workflow, and application releases.
• Detect quality degradation before production deployment.
• Integrate AI evaluation tests into CI/CD and release-management pipelines.
• Establish release gates based on defined quality and compliance thresholds.

6. Policy and Compliance Validation

• Translate employee support policies, procedures, and regulatory requirements into executable evaluation rules.
• Build automated checks for prohibited content, sensitive data handling, required disclosures, and escalation requirements.
• Ensure AI responses comply with applicable HR, privacy, security, legal, and corporate policies.
• Maintain audit trails for evaluations, overrides, approvals, and corrective actions.
• Support compliance reviews, audits, and evidence collection.
• Implement access controls and data-retention standards for evaluation data.

7. Human Evaluation Workflows

• Design reviewer interfaces and queues for human evaluation within Salesforce.
• Enable quality analysts and subject-matter experts to score, annotate, and classify responses.
• Support blind reviews, consensus scoring, adjudication, and reviewer calibration.
• Create task-routing logic based on risk, business domain, language, and evaluator expertise.
• Capture structured reviewer feedback for model and process improvement.
• Monitor reviewer agreement and evaluation consistency.

8. Quality Monitoring and Analytics

• Build dashboards and reports for AI quality and operational performance.
• Track metrics such as:
• Response accuracy rate
• Hallucination rate
• Policy compliance rate
• Regression failure rate
• Human escalation rate
• Reviewer agreement
• Employee satisfaction
• Resolution effectiveness
• Provide drill-down capabilities by model, release, use case, interaction type, and policy category.
• Develop alerts for quality threshold breaches and emerging failure patterns.
• Provide stakeholders with actionable insights and remediation recommendations.

9. Integration and Data Engineering

• Integrate Salesforce with AI platforms, large language models, knowledge systems, data warehouses, and analytics tools.
• Develop secure REST, event-driven, batch, and middleware-based integrations.
• Ingest conversation logs, model Clientdata, retrieval context, evaluation scores, and reviewer feedback.
• Ensure data quality, lineage, traceability, and reconciliation.
• Optimize data models and processing pipelines for high-volume evaluation workloads.
• Protect employee and enterprise data through appropriate security and privacy controls.

10. Testing, Deployment and Production Support

• Develop unit, integration, regression, performance, and security tests.
• Support user acceptance testing, release readiness, deployment, and hypercare.
• Troubleshoot Salesforce, integration, data, workflow, and evaluation-processing issues.
• Lead root-cause analysis for production incidents and quality failures.
• Implement preventive controls and technical improvements.
• Maintain operational documentation, runbooks, design specifications, and support procedures.

11. Cross-Functional Collaboration

• Partner with AI Engineering, Product Management, Data Science, Employee Experience, HR, Compliance, Legal, Security, and Quality teams.
• Translate business quality expectations into technical requirements and evaluation criteria.
• Participate in architecture reviews, sprint planning, backlog refinement, and release governance.
• Communicate risks, quality trends, technical decisions, and remediation plans.
• Provide technical leadership and knowledge transfer to engineering and support teams.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline.
• 5+ years of enterprise application development experience.
• 3+ years of hands-on Salesforce development experience.
• Strong experience with:
• Apex
• Lightning Web Components
• Salesforce Flow
• SOQL
• REST APIs
• Salesforce security and data models
• Experience building applications on Salesforce Service Cloud or Employee Service platforms.
• Experience designing automated testing or quality assurance frameworks.
• Strong knowledge of software engineering, integration, and CI/CD practices.
• Experience working with AI, machine learning, conversational AI, or large language model applications.
• Strong analytical, troubleshooting, and communication skills

Preferred Qualifications

• Experience building evaluation infrastructure for generative AI or conversational AI systems.
• Knowledge of AI evaluation concepts such as groundedness, relevance, factuality, hallucination detection, and model regression.
• Experience with Salesforce Einstein, Agentforce, Data Cloud, or comparable AI-enabled Salesforce capabilities.
• Experience integrating Salesforce with enterprise knowledge bases and AI platforms.
• Familiarity with Python, SQL, data pipelines, analytics platforms, and automated evaluation libraries.
• Knowledge of prompt management, retrieval-augmented generation, model observability, or LLM operations.
• Experience supporting HR, emplo"

Why Work With Us?

We believe in more than just jobs-we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter.

Our Commitment to Inclusion & Equity

Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics.

Awards & Recognition

• America's Most Honored Businesses (Top 10%)
• Fastest-Growing Staffing Firm by Staffing Industry Analysts
• INC 5000 List for Eight Consecutive Years
• Top 100 by Dallas Business Journal
• Spirit of Alliance Award by Agile1

Ready to Level Up Your Career?

Click Apply Now and let's make it happen.

Best regards,

Juan Carlos Matus

Sr. Customer Sucess Manager