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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in designing and deploying multi-agent systems, with a strong focus on Python, TypeScript, and Java. Proficient in implementing automated evaluation frameworks and ensuring compliance with security standards in enterprise environments.
Highest-signal resume keywords
Enterprise Software EngineeringProduction AI / LLM ExperienceLangGraph ExpertiseSalesforce API ExperienceAutomated Test Gates Implementation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonTypeScriptNode.jsJavaApexLangGraphLangChainPromptfooRagasDeepEval
Soft Skills
Exceptional Communication SkillsHigh Autonomy
Tools & Technologies
Salesforce APIsLangSmithLangfuseOpenTelemetryMCPCI/CD PipelinesContainerized MCP Deployments
Industry Keywords
Autonomous Agent SystemsRAG ArchitecturesSpecification-Driven DevelopmentLatency BottlenecksSecurity Compliance
Tech Stack
Tools & technologiesCloudJavaJavaScriptNode.jsPythonTypeScript
About the role
Key responsibilities & impact- Design and deploy stateful multi-agent coordination graphs using LangGraph or custom DAG loops
- Enable dynamic task decomposition, supervisor orchestration, human-in-the-loop escalation, and self-healing error recovery
- Build standardized Model Context Protocol (MCP) servers and connectors
- Securely expose Salesforce tools, custom objects, actions, and enterprise context to autonomous agent runners
- Architect multi-tiered LLM routing strategies across model tiers to balance latency, accuracy, and API costs
- Implement automated evaluation harnesses using Promptfoo, Ragas, and DeepEval within CI/CD pipelines
- Continuously measure context grounding, schema validity, and hallucination resistance against golden benchmark datasets
- Implement end-to-end telemetry and security using LangSmith or Langfuse
- Apply input sanitization, field-level security compliance, and automated PII scrubbing
- Establish specification-driven development patterns, clear API contracts, and architectural blueprints
- Communicate technical trade-offs directly to engineering teams and C-suite stakeholders
Requirements
What you’ll need- 7+ Years of Enterprise Software Engineering
- Proven experience building robust software systems in Python, TypeScript / Node.js, Java, or Apex
- 3+ Years of Production AI / LLM Experience
- Demonstrated track record designing, evaluating, and scaling production autonomous agent systems and RAG architectures in enterprise environments
- Deep expertise with LangGraph, LangChain, Anthropic / Claude APIs (tool calling, prompt caching, Claude Code), MCP, and observability suites (LangSmith, Langfuse, OpenTelemetry)
- Direct experience setting up automated test gates using Promptfoo, Ragas, or LLM-as-a-judge frameworks
- High autonomy to isolate complex latency bottlenecks, debug agent routing loops, and turn ambiguous enterprise needs into secure, deterministic technical realities
- Exceptional written and spoken English communication skills
- Legal authorization to work in the United States
- Hands-on experience with Salesforce APIs (REST, SOQL/SOSL, Platform Events), Salesforce Data Cloud, vector search, Agentforce, containerized MCP deployments, or Spec-Driven Development (SDD) is a strong plus
Benefits
Comp & perks- Competitive Pay ($190,000–$250,000 USD / year)
- Comprehensive Benefits Package (Medical, Dental, Vision & Retirement Plan)
- Holidays Off & Paid Time Off (PTO)
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- L1-L7 Career Framework
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety