Java FSD- GenAI
Dallas - Texas Plano TX or Charlotte NC or Seattle WA or Jersey City NJ
Full-Time Position
Job description
Role Summary
We are seeking a highly skilled GenAI Engineer to design build and operationalize nextgeneration AI solutions leveraging Large Language Models LLMs AI agents RetrievalAugmented Generation RAG architectures and scalable cloud platforms This role requires strong handson expertise across AI concepts model integration data pipelines and MLOpsCICD with the ability to translate business problems into productiongrade AI systems
Key Responsibilities
GenAI LLM Engineering
Design develop and deploy LLMpowered applications using leading foundation models OpenAI Azure OpenAI Anthropic opensource LLMs
Build LLMbased AI agents capable of multistep reasoning tool use orchestration and autonomous workflows
Implement and optimize agent frameworks LangChain LlamaIndex Semantic Kernel AutoGen CrewAI etc
Engineer robust prompting strategies memory mechanisms and toolaugmented reasoning
RAG Knowledge Systems
Design and implement RetrievalAugmented Generation RAG architectures
Build embedding pipelines using vector databases FAISS Pinecone Weaviate Azure AI Search Chroma
Optimize document ingestion chunking strategies metadata management and reranking
Ensure accuracy relevance and performance of AIgenerated responses
Machine Learning Model Integration
Apply practical ML concepts including classification clustering ranking and similarity search where applicable
Integrate traditional ML models with LLMbased systems for hybrid AI solutions
Evaluate finetune and test models using appropriate performance metrics
Data Engineering Pipelines
Develop and maintain data pipelines for structured and unstructured data using Python and SQL
Work with large datasets APIs and streamingbatch processing frameworks
Ensure data quality lineage observability and governance within AI workflows
MLOps CICD Productionization
Build CICD pipelines for AI and ML workloads including model versioning and automated testing
Deploy AI services in containerized environments Docker Kubernetes
Implement monitoring for model performance drift latency and cost
Ensure security access control and compliance for AI systems
Design and deploy AI solutions on cloud platforms such as AWS Azure or Google Cloud Platform
Leverage managed AIML services serverless components and scalable infrastructure
Optimize cost performance and reliability of AI workloads
Collaboration Stakeholder Engagement
Partner with product platform and business teams to translate requirements into AI solutions
Document architectures design decisions and operational runbooks
Provide guidance on GenAI best practices risks and responsible AI usage
Required Skills Experience
Never miss an opportunity! Create an alert based on the job you applied for.
