Consultant - FullStack

Role: Consultant - Full Stack Developer Experience: 2 to 3 Years Location: India - Delhi Key Responsibilities Design and implement full-stack enterprise applications using Python, FastAPI or Django, JavaScript/TypeScript, and React or SAPUI5. Develop RESTful APIs, asynchronous services, background workers, event-driven workflows, and microservices. Build AI-powered features using LLM APIs, open-source models, prompt engineering, embeddings, vector search, RAG, classification, summarization, extraction, and conversational interfaces. Implement document intelligence pipelines for PDF, DOCX, Excel, scanned documents, and structured or semi-structured business data. Create frontend applications with React, Next.js, TypeScript, HTML5, CSS3, or SAPUI5. Implement chat interfaces, document review screens, workflow dashboards, search interfaces, approval screens, and AI-generated results with citations or source traceability. Integrate AI services using REST APIs, SDKs, model gateways, structured output, function calling, and tool-based workflows. Build Python-based AI and data-processing services that integrate with SAP BTP applications. Integrate with SAP S/4HANA and other SAP systems using OData, SAP Gateway, and SAP Integration Suite. Work with SAP HANA Cloud for transactional data, analytical data, embeddings, and vector search. Integrate SAP AI Core, AI Launchpad, Generative AI Hub, SAP Business AI services, and SAP Document AI where applicable. Build intelligent workflows using SAP Build Process Automation and external workflow or orchestration platforms. Implement authentication and authorization using OAuth 2.0, JWT, SAML, role-based access control, and enterprise identity providers. Create unit, integration, API, UI, regression, and AI evaluation tests. Build CI/CD pipelines using GitHub Actions, GitLab CI, Azure DevOps, or equivalent tools. Containerize applications using Docker and deploy them on Kubernetes, Cloud Foundry, or managed cloud services. Monitor applications using structured logging, metrics, distributed tracing, health checks, and alerting. Participate in requirements analysis, technical design, estimation, code reviews, and production support. Maintain architecture documents, API specifications, data models, runbooks, test evidence, and requirements traceability artifacts. Follow secure coding, data privacy, responsible AI, and enterprise software-development practices. Required Technical Skills Backend and APIs Python 3.x. FastAPI, Django, Flask, or equivalent backend framework. REST APIs, OpenAPI, JSON, HTTP, WebSockets, and asynchronous programming. Pydantic, SQLAlchemy, Celery, Redis, or equivalent libraries. Experience with API versioning, pagination, validation, error handling, rate limiting, and authentication. Familiarity with microservices and event-driven architecture. Frontend JavaScript, React, Next.js, Angular, or SAPUI5. HTML5, CSS3, responsive design, and accessibility. State management, API integration, form validation, authentication flows, and frontend testing. Ability to create usable interfaces for AI results, confidence scores, citations, review queues, and human approvals. AI and Data Experience integrating LLMs through APIs or enterprise AI platforms like Ollama, HuggingFace. Familiarity with prompt engineering, embeddings, vector databases, RAG, semantic search, and document extraction. Knowledge of structured output, function calling, tool use, guardrails, hallucination mitigation, and prompt-injection protection. Familiarity with LangChain, LlamaIndex, Haystack, or comparable frameworks. Experience with PostgreSQL, MongoDB, Redis, Elasticsearch, Pinecone or FAISS. Understanding of model evaluation, regression testing, latency measurement, token usage, and response-quality monitoring. Machine Learning and Deep Learning Strong understanding of the machine learning and deep learning lifecycle, including: Data collection, cleaning, and transformation of unstructured data into structured formats Data preprocessing and Exploratory Data Analysis (EDA) Feature engineering Techniques (e.g. Feature Scaling, Handling Missing Values, Feature Creation, Feature Selection, Dimensionality Reduction etc) Model training, validation, testing - evaluation, and retraining Solid understanding of statistics, probability, and applied mathematics Understanding of data drift and model monitoring concepts Natural Language Processing (NLP), including Text analytics, OCR, Sentiment Analysis, Entity Recognition, Topic Modeling, etc. Transformer models including, Embedding Models and Sentence Transformers SAP BTP Working knowledge of SAP Business Technology Platform - SAP BTP Cloud Foundry. Familiarity with SAP HANA Cloud, SAP AI Core, AI Launchpad, Generative AI Hub, SAP Document AI, or SAP Business AI. Experience consuming or exposing OData and REST services. Exposure to SAPUI5, SAP Fiori, SAP Integration Suite, or SAP Build Process Automation is advantageous. Cloud and DevOps Docker and container-based application development - AWS, Microsoft Azure, Google Cloud, or SAP BTP. Git-based development and pull-request workflows, CI/CD pipeline development. Familiarity with Kubernetes, Cloud Foundry, or serverless deployments. Basic understanding of secrets management, networking, TLS, monitoring, and cloud cost management. Recommended Qualifications B.Tech/B.E. (in CSE, IT, AI-ML, Data Science-preferred but not restricted), 2+ years of enterprise experience in software development. Experience delivering at least one AI-enabled application or automation solution. Strong analytical, debugging, documentation, and communication skills. SAP BTP, SAP CAP, SAPUI5, cloud, or AI certification is beneficial.