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
Provide your feedback on BizChat
About Cognizant
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, provincial or local laws.
