Job summary
Extends the generative AI surface of Flowsource inside the client environment building Retrieval Augmented Generation RAG pipelines grounded on the clients own codebases knowledge bases and engineering standards configuring Code Companion developing prompt libraries and operating the Flowsource VS Code extension Evaluates LLM output quality against client coding conventions governs GitHub Copilot or equivalent integration and instruments Gen AI adoption metrics across the engineering org
Responsibilities
Key Responsibilities
Design and deploy RAG pipelines grounded on client codebases architecture docs ADRs runbooks and standards
Configure Flowsource Code Companion and the Flowsource VS Code extension for delivery teams tune retrieval chunking and reranking for the clients content corpus
Build and curate a client specific prompt library aligned to delivery patterns code generation refactoring test scaffolding code review assistants
Govern coexistence with GitHub Copilot or equivalent so the developer experience is coherent not competing
Run output quality evaluations coding standards conformance hallucination rate security PII leakage checks
Instrument Gen AI adoption metrics prompt volume acceptance rate token consumption per developer productivity proxies
Stay current on LLM choice for the client Bedrock Azure OpenAI on premise models and manage cost latency quality trade offs
Required Skills and Experience
5 plus years software engineering with at least 1 to 2 years building production RAG Gen AI systems
Hands on with LangChain or LlamaIndex vector databases eg pgvector OpenSearch Pinecone Azure AI Search
LLM API depth on at least one of AWS Bedrock or Azure OpenAI familiarity with GCP Vertex AI helpful
Strong Python comfort with TypeScript for VS Code extension extension points
Evaluation literacy building eval harnesses golden sets hallucination and bias testing
Awareness of enterprise AI governance data residency prompt logging PII handling
Flowsource Tooling and Tech Stack
Flowsource Code Companion and Flowsource VS Code extension
LLM APIs AWS Bedrock Azure OpenAI primary GitHub Copilot integration surface
Frameworks LangChain LlamaIndex
Vector DBs pgvector OpenSearch Elasticsearch Pinecone Azure AI Search
Python primary TypeScript extension surfaces
Success Metrics
Active developers using Code Companion weekly monthly
Prompt acceptance rate against baseline
Hallucination quality eval score on standing test set
Gen AI token consumption efficiency tokens per accepted output
Number of curated client validated prompts in the active library
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关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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