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Software Engineering SMTS
Salesforce. Design and build sophisticated agent architectures using Agentforce Builder, Agent Script, and NGA for production systems serving 15,000+ users .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building sophisticated agent architectures, implementing AI/ML frameworks, and optimizing performance for large-scale applications. Proficient in backend development, cloud infrastructure, and mentoring engineering teams to deliver impactful solutions.
Highest-signal resume keywords
Agentforce Builder ExperienceBackend Development in Java or PythonAI/ML Frameworks and Large Language ModelsCloud Infrastructure Experience (AWS, GCP)Prompt Engineering and RAG Architectures
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Backend DevelopmentJavaPythonAI/ML FrameworksLarge Language ModelsPrompt EngineeringData ProcessingAlgorithms and Data StructuresTest-Driven DevelopmentMicroservices Patterns
Soft Skills
Excellent Communication SkillsMentoring EngineersTechnical Guidance
Tools & Technologies
Salesforce Data CloudRESTful APIsGraphQLGitDockerKubernetesTerraformCI/CD PipelinesGrafanaDatadog
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Software Engineering
Industry Keywords
Conversational AIAgent Development PlatformsScalable Distributed SystemsContent ProcessingETL Pipelines
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsDockerETLGoogle Cloud PlatformGrafanaGraphQLHerokuJavaJenkinsKubernetesMicroservicesNode.jsPythonSpinnakerTerraformC++
About the role
Key responsibilities & impact- Design and build sophisticated agent architectures using Agentforce Builder, Agent Script, and NGA for production systems serving 15,000+ users
- Architect multi-node agent orchestration, sub-agent patterns, and agentic workflows for complex sales use cases
- Lead implementation of agent memory systems, context management, and conversation state handling
- Develop and optimize RAG patterns, retrieval strategies, and prompt engineering techniques
- Build scalable integrations connecting agents to Salesforce Data Cloud, Einstein, MuleSoft, external APIs, and MCP
- Design and implement content ingestion pipelines for structured and unstructured data
- Drive platform migrations while maintaining zero downtime for production systems
- Implement observability, monitoring, and debugging capabilities for agent systems
- Mentor junior engineers through code reviews, technical guidance, and knowledge sharing
- Make technical decisions on agent design, performance optimization, and scalability
- Lead design discussions, implementation, and delivery of major features in an Agentic Agile engineering model
- Participate in architecture reviews and technical roadmap planning
- Lead UAT efforts and production deployments
- Maintain high availability standards through bi-weekly release cycles
Requirements
What you’ll need- 6+ years of development experience as a software engineer
- Strong backend development experience in Java, Python, or an object-oriented compiled, statically-typed language such as C++, C#
- Deep knowledge of AI/ML frameworks and hands-on experience with large language models such as OpenAI, Anthropic, Claude, Gemini, or Llama
- Experience with prompt engineering, RAG architectures, and production LLM-based applications or agents
- Experience with conversational AI, chatbots, or agent development platforms
- Experience with cloud infrastructure such as AWS, GCP, or Heroku and scalable distributed systems
- Proficiency in data processing, vector databases, embeddings, semantic search, and retrieval optimization
- Strong understanding of Salesforce platform, including Apex, LWC, Data Cloud, and Platform Events, or equivalent enterprise platform experience
- Experience with RESTful APIs, GraphQL, event-driven architectures, and microservices patterns
- Bachelor's or Master's degree in Computer Science, Software Engineering, or related STEM field
- Strong competencies in algorithms and data structures
- Excellent verbal and written communication skills
- Strong experience in test-driven development, including unit, integration, and end-to-end testing for AI systems
- Ability to debug complex production issues, optimize performance, and resolve customer-impacting problems
- Experience with Git, Docker, Kubernetes, Terraform, CI/CD pipelines, Jenkins, GitHub Actions, or Spinnaker
- Track record of mentoring engineers
- Experience delivering large-scale features used by thousands of users with measurable business impact
- Agentforce or Agent Builder experience strongly preferred
- Experience with agent orchestration frameworks, multi-agent systems, and agentic AI architectures preferred
- Experience with prompt optimization, LLM fine-tuning, and model evaluation techniques preferred
- Experience with Customer Zero or early adopter programs preferred
- Knowledge of data engineering, ETL pipelines, and content processing at scale preferred
- Experience with Grafana, Datadog, and production agent monitoring preferred
- Contributions to technical communities, open-source projects, or conference speaking preferred
Benefits
Comp & perks- Time off programs
- Medical insurance
- Dental insurance
- Vision insurance
- Mental health support
- Paid parental leave
- Life insurance
- Disability insurance
- 401(k)
- Employee stock purchasing program
- Incentive compensation, equity, and benefits may be available for certain roles