Software Engineering SMTS

Leadout Capital; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Leadout Capital is seeking a Senior Software Engineer to design and implement high‑performance agent systems for enterprise-scale sales workflows. You will work with Agentforce, NGA, and Graph migrations while integrating with Salesforce Data Cloud and external platforms.

The role emphasizes hands-on coding, architecture leadership, and delivering scalable features for thousands of users with strong collaboration across teams.

Qualifications

• 6+ years of software development experience with increasing technical scope.
• Strong backend experience in Java and Python.
• Hands-on with AI/ML frameworks and LLMs such as OpenAI, Anthropic, Claude.

Responsibilities

• Design and build sophisticated agent architectures for production systems serving thousands of users.
• Architect multi-node orchestration and agentic workflows for complex use cases.
• Lead memory management, context handling, and conversation state for personalized experiences.
• Develop and optimize retrieval strategies, prompt engineering, and RAG patterns.

Skills

Backend development

Java

Python

AI/ML frameworks

LLMs / prompt engineering

Microservices

Mentoring

Education

Bachelor's or Master's in Computer Science or Software Engineering

Tools

Git

Docker

Kubernetes

Terraform

CI/CD pipelines (Jenkins, GitHub Actions)

Agentforce

Job description

The Experience

Agents and AI are fast evolving technologies. The Agentic Selling Team within Digital Experience Technology is building production AI agents that transform how Salesforce's global sales organization operates. As Customer Zero for Agentforce, we pioneer agent development patterns that influence product strategy and define enterprise AI standards. We are looking for a Senior Software Engineer who thrives in a fast-paced environment, delivers high-quality solutions independently, and drives technical excellence. You will architect and build sophisticated agent systems using Agentforce, Agent Script, and New Graph Architecture while integrating with Salesforce CRM, Data Cloud, and external platforms.

What You’ll Actually Be Doing

• 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 for personalized experiences
• Develop and optimize RAG patterns, retrieval strategies, and prompt engineering techniques to improve agent quality and accuracy
• Build scalable integrations connecting agents to Salesforce Data Cloud, Einstein, MuleSoft, and external APIs and MCP.
• Design and implement content ingestion pipelines processing structured and unstructured data (PDFs, web content, documents) for agent knowledge bases
• Drive platform migrations (e.g., Graph to Agent Script, legacy to NGA) while maintaining zero downtime for production systems
• Implement agent observability, monitoring, and debugging capabilities to track conversation quality and user satisfaction
• Mentor junior engineers through code reviews, technical guidance, and knowledge sharing
• Make critical technical decisions on agent design patterns, performance optimization, and scalability
• Work in an Agentic Agile engineering model leading design discussions, implementation, and delivery of major features
• Participate in architecture reviews and contribute to technical roadmap planning
• Lead UAT efforts, production deployments, and maintain high availability standards through bi-weekly release cycles

You’re Our Person If…

• 6+ years of development experience as a software engineer with demonstrated growth in technical complexity and scope
• Strong experience with backend development in Java, Python, or at least one object-oriented compiled, statically-typed language (C++, C#)
• Deep knowledge of AI/ML frameworks and hands-on experience working with large language models (e.g., OpenAI, Anthropic, Claude, Gemini, Llama)
• Proven experience with prompt engineering, RAG architectures, and building production LLM-based applications or agents
• Experience with conversational AI, chatbots, or agent development platforms (Agentforce experience strongly preferred)
• Experience with cloud infrastructure (e.g., AWS, GCP, Heroku) and designing scalable, distributed system architectures
• Proficiency in data processing, vector databases, embeddings, semantic search, and retrieval optimization
• Strong understanding of Salesforce platform (Apex, LWC, Data Cloud, 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 with strong competencies in algorithms and data structures
• Excellent verbal and written communication skills with ability to influence technical decisions and collaborate across organizations
• Strong experience in test-driven development including unit testing, integration testing, and end-to-end automation for AI systems
• Proven ability to debug complex production issues, optimize system performance, and resolve customer-impacting problems
• Experience with developer tools such as Git, Docker, Kubernetes, Terraform, CI/CD pipelines (Jenkins, GitHub Actions, Spinnaker)
• Track record of mentoring engineers and elevating team technical capabilities
• Experience delivering large-scale features used by thousands of users with measurable business impact

Even Better If…

• Hands-on experience building agents with Salesforce Agentforce or Agent Builder
• Experience with agent orchestration frameworks, multi-agent systems, and agentic AI architectures
• Deep expertise in prompt optimization, fine-tuning LLMs, and model evaluation techniques
• Experience with Customer Zero or early adopter programs influencing product development
• Knowledge of data engineering, ETL pipelines, and content processing at scale
• Experience with observability tools (Grafana, Datadog) and monitoring agent systems in production
• Contributions to technical communities, open-source projects, or conference speaking