Skills Required:
Kafka
Kubernetes
Dynatrace
Job Description:
Product Roadmap Modular Design
Define the product vision and roadmap for reusable Gen AI modules (e.g. RAG prompting frameworks hybrid MLLLM systems).
Architect parameterized business-agnostic solutions that abstract complexity (e.g. pre-configured prompts vector DB connectors chunking logic)
Design APIs and microservices to expose modules as reusable components (e.g. text-to-SQL service RAG-as-a-service).
Technical Leadership
Standardize patterns (e.g. prompt templates chunking strategies few-shot training pipelines) across use cases
Integrate LLM workflows (e.g. OpenAI Claude) with traditional ML (clustering classification) and enterprise systems (databases UI tools).
Optimize performance of Gen AI components (cost latency accuracy) and ensure scalability (e.g. load balancing for vector DBs).
Adoption Enablement
Develop documentation tutorials and sandbox environments for testing modules.
Train teams on best practices (e.g. prompt engineering security for LLM outputs)
Track metrics: Module reuse rate contribution volume time-to-deploy for new use cases.
Technical Expertise
Gen AI/ML Engineering
Hands-on experience with LLM integration (e.g. OpenAI Anthropic Llama 2) and frameworks (Lang Chain Llama Index).
Expertise in RAG workflows: Document chunking (sentence transformers) vector DBs (Pinecone FAISS) and hybrid search
Familiarity with text-to-SQL systems few-shot chain-of-thought prompting and traditional ML (clustering with scikit-learn Porch).
Software Engineering
Proficiency in Python API design (Fast API Flask) and cloud platforms (AWS Sage maker Azure AI).
Experience with CICD containerization (Docker) and infrastructure-as-code (Terraform).
UI Integration Skills
Frontend integration (React Streamlet for config UIs) and middleware (message queues auth systems like R2D2).
Product Strategy
Proven track record of building reusable MLAPI products or internal platforms.
Product Roadmap Modular Design
Define the product vision and roadmap for reusable Gen AI modules (e.g. RAG prompting frameworks hybrid MLLLM systems).
Architect parameterized business-agnostic solutions that abstract complexity (e.g. pre-configured prompts vector DB connectors chunking logic)
Design APIs and microservices to expose modules as reusable components (e.g. text-to-SQL service RAG-as-a-service).
Technical Leadership
Standardize patterns (e.g. prompt templates chunking strategies few-shot training pipelines) across use cases
Integrate LLM workflows (e.g. OpenAI Claude) with traditional ML (clustering classification) and enterprise systems (databases UI tools).
Optimize performance of Gen AI components (cost latency accuracy) and ensure scalability (e.g. load balancing for vector DBs).
Adoption Enablement
Develop documentation tutorials and sandbox environments for testing modules.
Train teams on best practices (e.g. prompt engineering security for LLM outputs)
Track metrics: Module reuse rate contribution volume time-to-deploy for new use cases.
Required Skills Experience
Technical Expertise
Gen AI/ML Engineering
Hands-on experience with LLM integration (e.g. OpenAI Anthropic Llama 2) and frameworks (Lang Chain Llama Index).
Expertise in RAG workflows: Document chunking (sentence transformers) vector DBs (Pinecone FAISS) and hybrid search
Familiarity with text-to-SQL systems few-shot chain-of-thought prompting and traditional ML (clustering with scikit-learn Porch).
Software Engineering
Proficiency in Python API design (Fast API Flask) and cloud platforms (AWS Sage maker Azure AI).
Experience with CICD containerization (Docker) and infrastructure-as-code (Terraform).
UI Integration Skills
Frontend integration (React Streamlet for config UIs) and middleware (message queues auth systems like R2D2).
Product Strategy
Proven track record of building reusable MLAPI products or internal platforms.
8 years of strong design development experience using C# .NET Core Web API Angular/React MVC
3 years of strong development experience using SQL Server/Oracle/Sybase complex procedures and SSIS/Resourcing experience in financial domain
Experience working with DevOps source code management tools like Git SVN Jira CI/CD Jenkins
Experience working with Agile/Scrum/RAD development methodology
Nice to have: container-based technologies like Docker Kubernetes OpenShift cloud platform and familiar with big-data and cloud-based technologies
Nice to have: experience in setting application in Linux/Windows IIS/Nginx
Nice to have: working experience with APAC Regulatory Reporting
Strong technical analytical skills to solve complex problems
Strategic thinker with excellent interpersonal skills to work across functions and businesses"
Hands-on working experience architecting Guidewire ClaimCenter solutions including customization and integration. Guidewire certification is a technologies of interest: Guidewire Cloud Salesforce CRM legacy modernization and AWS. Proven knowledge & architecture experience in architecture (digital / digital marketing / micro / macro / monolithic services APIs) application integration service-oriented architecture event-driven architecture application architecture distributed architecture data architecture and experience with modelling languages & techniques. Can quickly comprehend the functions and capabilities of new technologies. Can understand the long-term (big picture) and short-term perspectives of situations. Strong technical background (platforms languages protocols frameworks open source etc.).Experience with architecture frameworks (TOGAF) & architecture certifications a in engaging and supporting claims teams and understanding their day-to-day operations in the P&C insurance space. Open and clear connect with the business telecom infrastructure security audit vendors and software engineering. Driven by challenges and proactive and a motivation for on security standard methodologies and understand the impacts it can have on a working in a constantly evolving technological excellent teammate who demonstrates leadership. Comfortable speaking with all levels of the organization and different audiences.
Gen AI Engineer Kubernetes, Kafka, ML,Dynatrace
