工作职责:
We are looking fa Machine Engineer to support the development delivery of AI-enabled solutions fintelligent insurance product configuration.
This role will focus on developing integrating AI technologies such as Intelligent Document Processing, Retrieval-Augmented Generation , Large Language Models , prompt engineering AI workflows insurance product configuration management processes. The candidate will help improve how insurance product information, rules, documents business requirements are captured, structured, retrieved applied across the product lifecycle.
任职资格:
1. Python Development
In-depth expertise with Python fbackend development enterprise application design.
Strong experience designing, implementing consuming RESTful APIs using FastAPI similar frameworks.
Strong understanding of asynchronous programming (e.g., asyncio) fscalable AI-enabled applications.
Proven ability to write high-quality, maintainable well-tested production code using frameworks such as pytest.
Experience identifying performance bottlenecks, optimizing backend services ensuring system reliability in production environments.
Strong software engineering fundamentals, including clean architecture, modular design maintainable codebases.
2. AI Application Development
Proven experience applying Large Language Models (LLMs) to solve real business problems rather than building standalone AI demos.
Able to apply LLMs, RAG, Prompt Engineering, AI Agents AI Workflows to enterprise applications.
Strong understanding of AI application design, including identifying where AI should (should not) be applied within business processes.
Experience integrating AI capabilities enterprise systems such as knowledge retrieval, intelligent search, document understanding, workflow automation business assistants.
Ability to design AI-assisted workflows with appropriate validation, human-in-the-loop review fallback mechanisms.
Familiarity with OpenAI APIs, Azure OpenAI, Anthropic Claude, Google Gemini equivalent enterprise LLM platforms.
Experience evaluating AI application quality continuously improving prompt strategies, retrieval quality business outcomes.
3. Communication & Collaboration
Excellent communication skills with the ability to clearly articulate technical solutions to both technical non-technical stakeholders.
Able to explain AI capabilities, limitations implementation approaches in business-friendly language.
Strong ability to communicate architectural decisions, trade-offs technical recommendations effectively.
Comfortable working in cross-functional teams.
Able to communicate project progress, technical risks implementation plans clearly with teams
4. Infrastructure & DevOps
Experience deploying Python applications using Docker Kubernetes.
Familiarity with CI/CD pipelines using GitHub Actions, Jenkins similar platforms.
Experience troubleshooting production deployment issues across cloud hybrid environments.
Understanding of application security, configuration management secrets management best practices.
5. Monitoring & Production Excellence
Experience implementing logging, monitoring observability fproduction applications.
Ability to proactively identify production risks improve system reliability.
Focused on stable delivery, operational excellence continuous improvement.
Experience monitoring AI application quality identifying performance degradation in production.
6. Collaboration & Communication
Excellent communication skills with the ability to clearly explain technical solutions to both technical non-technical stakeholders.
Able to communicate design decisions, trade-offs architectural recommendations effectively.
Experience collaborating across Product, Business, Engineering AI teams to deliver enterprise solutions.
Comfortable working in cross-functional matrixganizations with multiple stakeholders.
Able to clearly communicate technical solutions with business teams management.
7. Learningientation
Strong curiosity towards emerging AI technologies enterprise software engineering practices.
Ability to rapidly learn new domains translate new technologies practical business value.
Continuously evaluates emerging AI capabilities identifies opportunities to improve engineering productivity business workflows.
Demonstrates strong ownership initiative in solving unfamiliar complex technical challenges.
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