Software Engineer I

The Core Infrastructure Compute team is responsible for managing and maintaining enterprise compute inventory, integrating and consolidating data from multiple sources, and ensuring data accuracy, consistency, and visibility across infrastructure platforms.

The team focuses on developing modern web applications, building scalable data integration and reporting solutions, leveraging Generative AI capabilities, and delivering actionable insights through advanced analytics and intelligent automation to drive operational efficiency, informed decision-making, and continuous infrastructure optimization.

We are seeking an experienced Senior Software Engineer with strong hands-on expertise in Microsoft Power BI, MS SQL Server, React.js, Python, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and data analytics.

The ideal candidate will possess strong software engineering fundamentals, programming expertise, analytical problem-solving capabilities, and practical experience designing and developing AI-enabled enterprise applications.

The role requires the ability to integrate structured and unstructured enterprise data with modern AI technologies while ensuring application scalability, security, reliability, and performance.

Software Engineering & Application Development Design, develop, enhance, and maintain scalable enterprise applications, analytical platforms, and AI-enabled solutions.

Develop modern, responsive, and interactive web applications using React.js, JavaScript, TypeScript, HTML, and CSS.

Build reusable frontend components, dashboards, and application interfaces.

Develop and integrate RESTful APIs, backend services, and enterprise data integrations.

Implement application functionality using Python, JavaScript, TypeScript, C#, or equivalent programming languages.

Apply software engineering best practices, including modular architecture, clean coding, unit testing, code reviews, and performance optimization.

Troubleshoot complex application, integration, performance, and production issues.

Collaborate with product owners, data engineers, AI engineers, and business stakeholders to deliver scalable technical solutions.

Power BI & Data Analytics Design, develop, deploy, and maintain enterprise Power BI dashboards, reports, and analytical solutions.

Translate complex business requirements into interactive dashboards, KPIs, scorecards, and actionable insights.

Develop Power BI semantic models, advanced DAX measures, calculated columns, and Power Query transformations.

Integrate Power BI with MS SQL Server, APIs, enterprise applications, and other structured data sources.

Optimize dashboard performance, data refresh processes, query execution, and reporting efficiency.

Implement row-level security, workspace access controls, and data governance best practices.

Analyze large datasets to identify trends, anomalies, operational risks, and opportunities for improvement.

Develop automated reporting and analytical solutions to improve business decision-making.

Explore AI-assisted analytics, natural-language querying, and intelligent insights across enterprise data.

MS SQL Server & Database Engineering Design, develop, maintain, and optimize SQL Server databases and enterprise data solutions.

Develop complex T-SQL queries, stored procedures, functions, views, and database scripts.

Perform query optimization, indexing, execution plan analysis, and database performance tuning.

Develop data extraction, transformation, and integration workflows to support applications, analytics, and AI use cases.

Implement relational data models and ensure data quality, consistency, integrity, and security.

Integrate SQL Server data with Power BI, React applications, Python services, and AI-powered applications.

Support structured data retrieval and integration with Generative AI and RAG solutions.

Troubleshoot database performance, connectivity, and data processing issues.

Generative AI & LLM Application Development Design, develop, and integrate Generative AI and Large Language Model (LLM) capabilities into enterprise applications.

Build AI-powered applications using Python and frameworks such as LangChain, LlamaIndex, or equivalent orchestration frameworks.

Integrate LLM APIs and enterprise AI platforms, including Azure OpenAI, OpenAI APIs, Google Vertex AI, or equivalent services.

Develop intelligent applications supporting natural-language search, document summarization, knowledge retrieval, conversational interfaces, and analytical insights.

Implement prompt engineering, structured outputs, tool/function calling, and context management techniques.

Develop reusable AI services and REST APIs for integration with React-based applications and enterprise platforms.

Evaluate LLM responses for accuracy, relevance, latency, cost, and reliability.

Implement guardrails, secure prompt handling, sensitive-data protection, and responsible AI practices.

Troubleshoot AI application issues involving model responses, context limitations, integration failures, and performance.

Retrieval-Augmented Generation (RAG) & Vector Databases Design, develop, implement, and optimize Retrieval-Augmented Generation (RAG) solutions using enterprise structured and unstructured data.

Build document ingestion, preprocessing, chunking, embedding generation, indexing, retrieval, and response generation pipelines.

Work with vector databases such as Pinecone, Milvus, Weaviate, Chroma, FAISS, or PostgreSQL with pgvector.

Implement semantic search, similarity search, metadata filtering, and hybrid retrieval techniques.

Integrate vector databases with LLMs, Python services, and enterprise knowledge repositories.

Develop enterprise knowledge assistants, document search applications, and AI-powered question-answering solutions.

Implement embedding models, vector indexing strategies, retrieval optimization, and reranking techniques.

Improve RAG response quality through retrieval evaluation, grounding, c