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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building LLM-powered applications and integrating AI capabilities into enterprise workflows, with a strong focus on maintaining high code quality and effective documentation. Proficient in implementing solutions that capture outcome data and support capability-building for sustainable operations.
Highest-signal resume keywords
LLM-Powered Application DevelopmentRAG Pipeline ConstructionAI Integration via APIsProficiency in Python, Java, TypeScript/JavaScriptExperience with AWS, Azure, or GCP
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 EngineeringPrompt EngineeringContext ManagementData Modelling PrinciplesCI/CDTDDCode ReviewRelational StoresColumnar StoresVector Stores
Soft Skills
Clear CommunicationCollaboration with Technical Peers
Industry Keywords
Agentic AI SolutionsObservabilityAgent WorkflowsTool-Augmented AgentsOutcome Data Capture
Tech Stack
Tools & technologiesAWSAzureGoogle Cloud PlatformJavaJavaScriptPythonSDLCSQLTypeScript
About the role
Key responsibilities & impact- Build prototypes and proofs of concept and ship agentic AI solutions to production standards
- Implement and test tool use, retrieval pipelines, and agent workflows
- Contribute to evaluation, observability, and guardrails for agentic systems
- Integrate AI capabilities into existing enterprise workflows and systems
- Maintain high code quality and documentation for reusable patterns
- Flag technical risks and blockers early
- Interface with technical peers to finalize requirements and complete moderately complex bug fixes
- Build reusable solutions, patterns, reference implementations, and starter kits
- Implement solutions to capture outcome data against baselines
- Work alongside host-function stakeholders to ensure builds fit real workflows
- Support handover and capability-building so solutions remain owned and operable after the squad moves on
Requirements
What you’ll need- 3+ years in software engineering
- Hands-on experience building LLM-powered applications in production, including RAG, tool-augmented agents, or agentic workflows
- Experience building RAG pipelines, tool-augmented agents, and agentic workflows
- Familiarity with prompt engineering, context management, evaluation, and observability
- Understanding of agent memory, tools, and retrieval for multi-step tasks
- Experience integrating AI into existing systems via APIs and data pipelines
- Experience with AWS, Azure, or GCP
- Knowledge of CI/CD, modern SDLC, TDD, and code review
- Experience with relational, columnar, and vector stores
- Sound data-modelling principles
- Proficiency in Python, Java, TypeScript/JavaScript, SQL, and relevant AI SDKs
- Clear written and verbal communication with technical peers and stakeholders
- Experience instrumenting solutions to capture usage, productivity, and quality metrics against established baselines
Benefits
Comp & perks- Comprehensive Pension Plan
- Generous vacation entitlement and option for sabbatical leave
- Maternity, Paternity, Adoption and Family Care leave
- Personal Choice budget
- Internal communities and networks
- Various employee discounts
- Recruitment introduction reward
- Employee Assistance Program (global)
- Flexible working hours
- Wellbeing initiatives
- Shared parental leave
- Study assistance
- Sabbaticals
- Annual incentive bonus