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Sr Consultant - Full Stack Developer

  • Source: Naukri
  • Invenio Global
  • On-site
  • Delhi
  • Full-Time
  • Senior

Job Description

Role: Senior Consultant - Full Stack Developer
Experience: 5 to 8 Years
Location: India - Delhi

Experience

The candidate must have experience taking products from requirements and architecture through development, testing, deployment, production operations, enhancement, and stakeholder adoption with at least 3-4 complete, end-to-end production implementations.

Bachelor s or master s degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related discipline.

Core responsibilities

Architecture and technical leadership

  • Own the technical architecture of AI-enabled enterprise products from discovery to production.
  • Define application boundaries, service contracts, data models, integration patterns, deployment topology, and non-functional requirements.
  • Select appropriate technologies for LLM orchestration, data processing, vector search, workflow automation, and enterprise integration.
  • Produce architecture decision records, solution blueprints, sequence diagrams, API specifications, threat models, capacity plans, and operational runbooks.
  • Establish reusable reference architectures for RAG, AI agents, human-in-the-loop review, model gateways, and workflow automation.
  • Define standards for API design, schema validation, error handling, observability, testing, secure coding, versioning, and release management.
  • Review designs and code produced by other engineers.
  • Lead proof-of-concepts and convert successful prototypes into production-grade implementations.
  • Balance functional requirements, performance, reliability, security, cost, maintainability, and delivery timelines.

Full-stack engineering

  • Develop high-performance Python services using FastAPI, Django, Flask, or equivalent frameworks.
  • Build asynchronous processing pipelines using Kafka, Redis Streams, AWS SQS/SNS, Azure Service Bus, or equivalent technologies.
  • Develop frontend applications using React, Next.js, JavaScript, HTML5, CSS3, and/or SAPUI5.
  • Build enterprise dashboards, AI workbenches, workflow consoles, document-review interfaces, search applications, approval journeys, and administrative tools.
  • Implement streaming AI responses, structured result views, confidence indicators, citations, source references, audit trails, and human feedback mechanisms.
  • Design and implement analytical, document, metadata, and vector data stores.
  • Build reusable shared libraries, SDKs, frontend components, API clients, authentication modules, and platform services.
  • Develop secure integrations with internal systems, third-party services, data platforms, and enterprise identity providers.

AI and agentic systems

  • Design and productionize RAG systems using document ingestion, chunking, metadata enrichment, embeddings, reranking, retrieval filters, and response generation.
  • Implement AI agents and tool-using workflows with controlled planning, execution, validation, retries, approvals, and escalation.
  • Integrate LLMs from approved providers and model platforms, including enterprise model gateways and SAP Generative AI Hub where applicable.
  • Implement prompt versioning, model versioning, evaluation datasets, golden test cases, regression suites, and quality gates.
  • Establish controls for hallucination, prompt injection, data leakage, unsafe tool use, unauthorized access, and excessive model autonomy.
  • Design model fallback, timeout, retry, caching, token-budget, and cost-control strategies.
  • Implement observability for prompts, responses, model metadata, tool calls, latency, token usage, retrieval quality, user feedback, and failure modes.
  • Collaborate with data scientists and platform engineers on model training, fine-tuning, inference optimization, deployment, and monitoring.
  • Build AI features that support structured extraction, classification, summarization, recommendations, forecasting, conversational search, and business-process automation.

SAP BTP and enterprise SAP responsibilities

  • Lead the design and implementation of SAP BTP extension and side-by-side applications.
  • Design integrations between SAP BTP, SAP S/4HANA, SAP ECC, SAP SuccessFactors, SAP Ariba, SAP Analytics Cloud, and non-SAP systems.
  • Use OData, REST, RFC, events, SAP Gateway, and SAP Integration Suite as appropriate.
  • Work with SAP BTP services such as:
    • SAP HANA Cloud, SAP AI Core, SAP AI Launchpad, SAP Generative AI Hub, SAP Integration Suite.
    • SAP Destination and Connecti…

Skills

  • Python
  • FastAPI
  • Django
  • Flask
  • Kafka
  • Redis
  • amazon-web-services
  • amazon-sqs
  • amazon-sns
  • microsoft-azure
  • azure-service-bus
  • microsoft-azure-service-bus
  • React
  • next-js
  • javascript
  • HTML5
  • css-3
  • aws-sdks
  • sap
  • sap-s4hana
  • sap-ecc-r3
  • successfactors
  • sap-successfactors
  • sap-ariba
  • sap-analytics-cloud
  • odata
  • sap-gateway
  • sap-hana
  • launchpad
  • cloud-foundry
  • sqlalchemy
  • TypeScript
  • microsoft-typescript
  • NodeJS
  • GraphQL
  • open-api
  • PostgreSQL
  • MongoDB
  • Elasticsearch
  • opensearch
  • JSON
  • guardrails
  • benchmark
  • LangChain
  • LlamaIndex
  • haystack
  • document-ai
  • oauth
  • openid-connect
  • google-cloud-platform
  • Docker
  • Kubernetes
  • Github
  • github-actions
  • gitlab
  • azure-devops
  • opentelemetry
  • create-lms

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