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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and developing agentic AI systems, with a strong focus on LLM development practices, cloud-native architectures, and integrating complex workflows. Proven ability to lead technical teams, mentor developers, and translate business requirements into scalable AI-driven solutions.
Highest-signal resume keywords
Agentic AI Systems DevelopmentLLM Development PracticesCloud-Native ArchitecturesMCP-Based IntegrationsTechnical Leadership
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Python DevelopmentProduction-Grade ApplicationsMulti-Step ReasoningWorkflow ExecutionModel-Driven Decision LogicVersion ControlCI/CD PracticesAutomated TestingDeployment AutomationAgent Orchestration Frameworks
Soft Skills
MentoringCommunicationProblem-Solving
Tools & Technologies
AzureAWSGCPDatabricksSnowflakeSparkGitGitHubAPIsMicroservices
Certifications & Qualifications
Public Trust Clearance
Industry Keywords
LLMOpsMLOpsHIPAA ComplianceData GovernanceSensitive Data Handling
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformMicroservicesPythonSpark
About the role
Key responsibilities & impact- Architect, develop, and operationalize next-generation agentic systems powered by advanced LLMs and MCP frameworks
- Build intelligent, multi-step, tool-using agents that autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem
- Design and implement agent orchestration frameworks
- Integrate model-driven decision logic
- Build robust, production-grade agent capabilities using emerging AI techniques
- Provide technical leadership and explore cutting-edge agentic patterns
- Drive proof-of-concept innovation
- Partner with engineering and product teams to translate experimental architectures into real-world impact
Requirements
What you’ll need- Minimum of 8 years with BS/BA; minimum of 6 years with MS/MA; minimum of 3 years with PhD
- Strong software engineering background with deep experience building production-grade applications and services
- Expertise developing agentic AI systems, including planning, tool-use, multi-step reasoning, workflow execution, or autonomous decisioning logic
- Hands-on experience designing and implementing MCP-based integrations, tool interfaces, or model-driven service frameworks
- Ability to translate ambiguous business or mission requirements into scalable AI-driven solutions
- Proficiency with LLM development practices including fine-tuning, RAG integration, prompt engineering, and interaction models for agent workflows
- Strong Python development skills and familiarity with distributed compute environments, APIs, microservices, and cloud-native architectures
- Experience integrating agents or LLM-driven components into Azure, AWS, GCP, or large-scale data ecosystems
- Understanding of LLMOps/MLOps principles including versioning, testing, deployment automation, monitoring, and governance
- Demonstrated ability to lead solution design, mentor developers, and communicate complex AI architectures to technical and non-technical stakeholders
- Version control and modern CI/CD practices, including Git/GitHub, automated testing, deployment pipelines, and release management
- US Citizen with the ability to obtain/maintain a Public Trust clearance
- Preferred: experience building multi-agent systems, agent swarms, or coordinated reasoning frameworks
- Preferred: familiarity with advanced tool-calling strategies, dynamic tool selection, function-call planning, or graph-structured task planners
- Preferred: experience with structured LLM evaluation methods, agent benchmarking, or test harnesses
- Preferred: knowledge of LLM and agent performance optimization, including caching, model distillation, model routing, or accelerated inference
- Preferred: background integrating agentic components with Databricks, Snowflake, Spark, or similar platforms
- Preferred: hands-on experience developing innovative POCs or experimental agentic architectures in R&D environments
- Preferred: familiarity with Strands Agents, LangGraph, CrewAI, or similar frameworks
- Preferred: exposure to safety-oriented design patterns, including guardrails, validation layers, or constrained-action frameworks
- Preferred: experience designing secure, compliance-aware systems handling sensitive data under HIPAA and federal security standards, including encryption, access controls, auditability, and governance for PHI
Benefits
Comp & perks- Employees may be eligible for overtime
- Employees may be eligible for shift differential
- Employees may be eligible for a discretionary bonus
- Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law