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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing agentic AI systems, with a strong foundation in software engineering and experience in LLM orchestration and cloud-native architecture. Capable of coaching teams and evaluating AI outputs while leveraging emerging technologies for practical applications.
Highest-signal resume keywords
Software EngineeringLLM OrchestrationCloud-Native ArchitecturePython CodingLow-Code Automation Tools
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringDistributed SystemsLLM OrchestrationAgent FrameworksRAGPythonNode.jsAPI ManagementCloud-Native ArchitectureDebugging Non-Deterministic Systems
Soft Skills
Coaching TeamsExplaining Complex Ideas
Tools & Technologies
N8nGCPAWS
Certifications & Qualifications
Degree in Computer ScienceDegree in Engineering
Industry Keywords
Agentic AIAI Automation HubEvaluation FrameworksEmerging AI Technologies
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsGoogle Cloud PlatformJavaScriptNode.jsPython
About the role
Key responsibilities & impact- Design and ship agentic AI systems in production
- Build agents, retrieval pipelines and automations
- Prototype quickly and demonstrate possibilities with working demos
- Implement solutions in line with MPB’s agentic reference architecture
- Work as a peer with the AI Product Manager and Lead Decision & AI Scientist
- Help evaluate LLM outputs
- Select appropriate models while balancing budget and value
- Coach teams across MPB experimenting with AI
- Monitor emerging AI technologies and identify worthwhile opportunities
- Help establish and shape MPB’s new AI Automation Hub and its centre of excellence for agentic AI
Requirements
What you’ll need- Strong software engineering background, with complex, distributed systems shipped to production
- Hands-on experience with LLM orchestration, agent frameworks and RAG
- Experience with low-code automation tools such as n8n
- Confident coding in Python or Node.js
- Experience with cloud-native architecture using GCP or AWS
- Experience with API management and robust backend pipelines
- Structured, pragmatic approach to debugging non-deterministic systems
- Ability to explain complex ideas through working demonstrations
- Experience defining evaluation frameworks for LLM outputs (nice to have)
- Degree in Computer Science, Engineering or a related field, or equivalent experience (nice to have)
- Experience coaching or influencing teams without formal authority (nice to have)
- Track record of turning emerging AI tooling into practical opportunities (nice to have)
Benefits
Comp & perks- Access to MPB’s Learning Lab
- Thousands of free courses
- Low-hierarchy, high-trust peer-led work environment
- Real ownership and autonomy
- Opportunity to help define a brand-new function
- Purpose-driven work supporting accessibility and sustainability in photography equipment
- Opportunity to work for a business scaling across three markets
- Hybrid working arrangement