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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in AI and agentic architecture, with a strong focus on Python, APIs, and distributed systems. Proven ability to lead technical delivery across multiple teams while implementing AI-assisted engineering practices and ensuring compliance with regulated data products.
Highest-signal resume keywords
10+ Years In Software Engineering4+ Years Leading AI And Agentic ArchitectureStrong Python SkillsExperience With AWS And Amazon BedrockExperience With CI/CD And Cloud Deployment
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonAPIsDistributed SystemsAgent OrchestrationRAGCI/CDEvaluationObservabilitySemantic LayersKnowledge Graphs
Soft Skills
Ability To Explain Trade-OffsInfluencing Technical Stakeholders
Tools & Technologies
AWSAmazon BedrockAgentCoreLangGraphStandsMCP
Industry Keywords
AI-Enabled SDLC PracticesRegulated Data ProductsInsurance
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsPythonSDLC
About the role
Key responsibilities & impact- Define reference architectures, reusable agent services, and engineering standards
- Select models, frameworks, and build-versus-buy options based on quality, cost, and business needs
- Write production code, review designs and pull requests, resolve complex technical issues, and coach teams
- Implement tool calling, orchestration, context and memory, retries, execution limits, and human approvals
- Build agentic, retrieval-augmented generation, structured data access, and API or MCP integrations
- Establish AI evaluation datasets, task-success measures, groundedness, tool-call accuracy, adversarial testing, and release criteria
- Implement CI/CD, versioning, monitoring, agent tracing, fallbacks, and rollback
- Track reliability, latency, and cost per successful task; support incident resolution
- Apply least-privilege access, sensitive-data protection, prompt-injection defenses, auditability, and approval controls
- Introduce and govern AI-assisted engineering practices such as coding agents, AI code review, and test generation
- Prioritize use cases with Product, maintain the technical roadmap, and share reusable components and lessons across teams
Requirements
What you’ll need- 10+ years in software engineering
- 4+ years leading AI and agentic architecture or technical delivery across multiple teams, or equivalent demonstrated expertise
- Deployed and operated multiple LLM or agentic applications in production
- Strong Python, APIs, distributed systems, RAG, and agent orchestration skills
- Experience with cloud deployment, containers, CI/CD, evaluation, and observability
- Ability to explain trade-offs and influence technical and business stakeholders
- Experience with AWS and Amazon Bedrock, including AgentCore
- Experience with LangGraph, Stands, or comparable agent frameworks
- Experience with MCP
- Experience with semantic layers, ontologies, or knowledge graphs
- Experience with insurance or other regulated data products
- Experience with AI-enabled SDLC practices
Benefits
Comp & perks- Health Insurance
- Retirement Plan
- Disability benefits
- Paid Time Off program
- Competitive total rewards package
- Work flexibility
- Support, coaching, and training