SAP Fullstack Developer

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.