{"id":2606971,"url":"https://alion.io/job/american-express-software-engineer-ii-33","title":"Software Engineer II","company":{"id":2209,"name":"American Express","domain":"americanexpress.com","url":"https://alion.io/company/american-express","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":100,"open_postings":48,"ghost_share":0,"stale_share":0.063,"repost_share":0.167,"time_to_fill_p50_days":7,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"C#","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hallucination","optional":false},{"name":"JavaScript","optional":false},{"name":"Jenkins","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Milvus","optional":false},{"name":"MS SQL","optional":false},{"name":"Node JS","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"PowerShell","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"Dimensional Modeling","optional":true}],"status":"live","first_seen_at":"2026-10-15T05:48:10Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T13:26:42Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"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.\nWe 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.\nThe 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.\n Software Engineering & Application Development\nDesign, develop, enhance, and maintain scalable enterprise applications, analytical platforms, and AI-enabled solutions.\nDevelop modern, responsive, and interactive web applications using React.js, JavaScript, TypeScript, HTML, and CSS.\nBuild reusable frontend components, dashboards, and application interfaces.\nDevelop and integrate RESTful APIs, backend services, and enterprise data integrations.\nImplement application functionality using Python, JavaScript, TypeScript, C#, or equivalent programming languages.\nApply software engineering best practices, including modular architecture, clean coding, unit testing, code reviews, and performance optimization.\nTroubleshoot complex application, integration, performance, and production issues.\nCollaborate with product owners, data engineers, AI engineers, and business stakeholders to deliver scalable technical solutions.\nPower BI & Data Analytics\nDesign, develop, deploy, and maintain enterprise Power BI dashboards, reports, and analytical solutions.\nTranslate complex business requirements into interactive dashboards, KPIs, scorecards, and actionable insights.\nDevelop Power BI semantic models, advanced DAX measures, calculated columns, and Power Query transformations.\nIntegrate Power BI with MS SQL Server, APIs, enterprise applications, and other structured data sources.\nOptimize dashboard performance, data refresh processes, query execution, and reporting efficiency.\nImplement row-level security, workspace access controls, and data governance best practices.\nAnalyze large datasets to identify trends, anomalies, operational risks, and opportunities for improvement.\nDevelop automated reporting and analytical solutions to improve business decision-making.\nExplore AI-assisted analytics, natural-language querying, and intelligent insights across enterprise data.\nMS SQL Server & Database Engineering\nDesign, develop, maintain, and optimize SQL Server databases and enterprise data solutions.\nDevelop complex T-SQL queries, stored procedures, functions, views, and database scripts.\nPerform query optimization, indexing, execution plan analysis, and database performance tuning.\nDevelop data extraction, transformation, and integration workflows to support applications, analytics, and AI use cases.\nImplement relational data models and ensure data quality, consistency, integrity, and security.\nIntegrate SQL Server data with Power BI, React applications, Python services, and AI-powered applications.\nSupport structured data retrieval and integration with Generative AI and RAG solutions.\nTroubleshoot database performance, connectivity, and data processing issues.\nGenerative AI & LLM Application Development\nDesign, develop, and integrate Generative AI and Large Language Model (LLM) capabilities into enterprise applications.\nBuild AI-powered applications using Python and frameworks such as LangChain, LlamaIndex, or equivalent orchestration frameworks.\nIntegrate LLM APIs and enterprise AI platforms, including Azure OpenAI, OpenAI APIs, Google Vertex AI, or equivalent services.\nDevelop intelligent applications supporting natural-language search, document summarization, knowledge retrieval, conversational interfaces, and analytical insights.\nImplement prompt engineering, structured outputs, tool/function calling, and context management techniques.\nDevelop reusable AI services and REST APIs for integration with React-based applications and enterprise platforms.\nEvaluate LLM responses for accuracy, relevance, latency, cost, and reliability.\nImplement guardrails, secure prompt handling, sensitive-data protection, and responsible AI practices.\nTroubleshoot AI application issues involving model responses, context limitations, integration failures, and performance.\nRetrieval-Augmented Generation (RAG) & Vector Databases\nDesign, develop, implement, and optimize Retrieval-Augmented Generation (RAG) solutions using enterprise structured and unstructured data.\nBuild document ingestion, preprocessing, chunking, embedding generation, indexing, retrieval, and response generation pipelines.\nWork with vector databases such as Pinecone, Milvus, Weaviate, Chroma, FAISS, or PostgreSQL with pgvector.\nImplement semantic search, similarity search, metadata filtering, and hybrid retrieval techniques.\nIntegrate vector databases with LLMs, Python services, and enterprise knowledge repositories.\nDevelop enterprise knowledge assistants, document search applications, and AI-powered question-answering solutions.\nImplement embedding models, vector indexing strategies, retrieval optimization, and reranking techniques.\nImprove RAG response quality through retrieval evaluation, grounding, citation generation, and hallucination reduction.\nIntegrate SQL Server and other enterprise data sources with RAG workflows where appropriate.\nImplement document-level access controls, data isolation, secure retrieval, and appropriate handling of confidential enterprise information.\nMonitor and optimize retrieval accuracy, response latency, token usage, and overall AI application performance.\nProgramming, Automation & API Integration\nDevelop automation solutions using Python, JavaScript, TypeScript, PowerShell, and SQL.\nBuild backend services and APIs using frameworks such as FastAPI, Flask, Node.js, or equivalent technologies.\nAutomate data ingestion, validation, transformation, reporting, and operational workflows.\nDevelop reusable scripts and components for AI applications, analytics platforms, and enterprise integrations.\nIntegrate REST APIs, LLM APIs, vector databases, SQL Server, and frontend applications.\nImplement error handling, logging, exception management, and automated testing.\nSupport CI/CD pipelines using GitHub Actions, Jenkins, Azure DevOps, or equivalent tools.\nApply version control, secure coding standards, and automated deployment practices.\nAnalytical Problem Solving & Intelligent Solutions\nAnalyze complex business and technical problems and translate requirements into scalable software and analytical solutions.\nDevelop data-driven insights using SQL, Power BI, Python, and AI-assisted analytical techniques.\nIdentify opportunities to apply Generative AI, semantic search, RAG, and intelligent automation to enterprise workflows.\nPerform data profiling, reconciliation, anomaly detection, and root cause analysis.\nEvaluate AI use cases based on feasibility, business value, security, accuracy, and operational impact.\nCollaborate with stakeholders to define KPIs, reporting requirements, and intelligent application capabilities.\nCommunicate technical findings and analytical insights effectively to technical and non-technical audiences.\n Required Experience & Technical Skills\n3-5 years of overall IT, software engineering, application development, or data analytics experience, with hands-on experience in modern application development and AI technologies.\nStrong hands-on experience with Microsoft Power BI, including DAX, Power Query, semantic modeling, dashboard development, and Power BI Service.\nExtensive experience with MS SQL Server and T-SQL, including complex queries, stored procedures, views, database design, and performance optimization.\nStrong hands-on expertise in React.js, JavaScript, TypeScript, HTML, and CSS.\nStrong programming experience in Python, including API development, automation, data processing, and integration.\nSolid understanding of software engineering principles, data structures, algorithms, object-oriented programming, and design patterns.\nHands-on experience developing Generative AI and LLM-powered applications.\nPractical knowledge of Retrieval-Augmented Generation (RAG) architecture, implementation, and optimization.\nExperience working with vector databases such as Pinecone, Milvus, Weaviate, Chroma, FAISS, or pgvector.\nUnderstanding of embeddings, semantic search, vector similarity, document chunking, retrieval strategies, and context augmentation.\nExperience with LangChain, LlamaIndex, or equivalent LLM application frameworks.\nExperience integrating LLM APIs, REST services, enterprise databases, and frontend applications.\nStrong understanding of data analytics, data modeling, data transformation, and reporting solutions.\nExperience with Git, CI/CD pipelines, automated testing, and Agile software development practices.\nKnowledge of secure application development, data privacy, authentication, authorization, and enterprise AI governance.\nStrong analytical thinking, debugging, troubleshooting, and problem-solving capabilities.\nAbility to independently design, develop, deploy, and support enterprise-grade software and AI-enabled solutions.\nPreferred Qualifications\nKnowledge of data warehousing, dimensional modeling, and enterprise data governance.\nExperience building AI-powered dashboards, conversational analytics, or natural-language interfaces for enterprise data.\nExperience developing applications in large-scale, highly regulated environments.","description_format":"text","description_chars":10260,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Cards & Card Issuing","Payment Processing & Gateways"],"lifecycle":[{"event":"open","at":"2026-10-15T10:03:36Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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