GenAI Full Stack Developer- India (PL854)
Paralucent
IndiaremotePosted 1 month ago
Skill Required
GenAI-DeveloperFull-Stack-DeveloperAI-EngineerBackend-EngineerCloud-EngineerAI-Full-Stack-DeveloperFull-Stack-AI-DeveloperAI-Full-Stack-EngineerFull-Stack-AI-EngineerGenAI-Software-EngineerSenior-Full-Stack-AI-DeveloperGenerative-AI-EngineerFull Stack DeveloperGenerative AIsoftware engineeringSystem DesignServerlessGitHub ActionsMicroservicesElasticsearchObservabilityCD pipelinesLangChainEngineeringR ProgrammingTypeScriptPostgreSQLKubernetesSalesforceServiceNowSharePointautomationTerraformdesigningTailwindsecuritybuildingRAGContract
Key highlights
- 3 to 8+ years of full stack software engineering experience
- 12 Month Contract
- Remote work
- Deep hands-on experience building production-grade RAG systems and LLM-enabled applications
Role overview
Our client is seeking a GenAI Full Stack Developer to design, build, and scale enterprise AI applications powered by Large Language Models, Retrieval-Augmented Generation (RAG), and Azure-native cloud services. This role is ideal for someone with strong backend engineering and system design capability who enjoys building production-grade AI systems across the full stack. You will work closely with product, UX, platform, and engineering teams to deliver secure, scalable, and reliable AI-powered applications with a strong focus on performance, maintainability, and responsible AI practices.
Responsibilities
- Build and maintain modern web applications using React, Angular, or similar frameworks
- Design and develop scalable backend APIs and AI orchestration services using advanced Python, FastAPI, Java, or .NET
- Develop cloud-native and serverless applications using Azure services such as Azure Functions, API Management, Logic Apps, and Azure Service Bus
- Implement secure authentication and authorisation systems including OAuth2, OpenID Connect, JWT, and RBAC
- Apply software engineering best practices including testing, CI/CD, documentation, code reviews, and modular architecture
- Design and implement AI-powered capabilities such as assistants, semantic search, summarisation, workflow automation, and intelligent retrieval systems
- Build and optimise enterprise-grade RAG architectures including ingestion pipelines, chunking strategies, embeddings, vector search, hybrid retrieval, reranking, grounding, and hallucination mitigation
- Integrate with LLM providers and orchestration frameworks including Azure OpenAI, OpenAI, Anthropic, Hugging Face, LangChain, Semantic Kernel, or LlamaIndex
- Develop prompt engineering strategies, tool/function calling workflows, guardrails, moderation pipelines, and output validation systems
- Implement observability and evaluation mechanisms for monitoring LLM quality, latency, and reliability
- Integrate AI applications with enterprise systems such as SharePoint, Salesforce, ServiceNow, and internal APIs
- Develop data ingestion, enrichment, transformation, and retrieval pipelines
- Work with relational, NoSQL, and vector databases including PostgreSQL, Redis, Azure AI Search, Pinecone, Elasticsearch, or similar technologies
- Ensure strong governance, privacy, and security controls for enterprise and sensitive data
- Optimise LLM performance, scalability, latency, and operational cost through caching, batching, streaming, and token optimisation
- Design resilient distributed systems using retries, fallbacks, circuit breakers, and graceful degradation patterns
- Implement logging, monitoring, tracing, and observability solutions using OpenTelemetry, Application Insights, Grafana, or similar tooling
- Apply responsible AI principles including privacy controls, auditability, bias mitigation, and secure AI implementation practices
- Participate in system design discussions and contribute to scalable cloud architecture decisions
Requirements
- 3 to 8+ years of full stack software engineering experience
- Advanced Python programming and backend engineering capability
- Deep hands-on experience building production-grade RAG systems and LLM-enabled applications
- Strong experience with Azure-native architecture and serverless services
- Strong understanding of REST APIs, microservices, distributed systems, and cloud-native design
- Experience designing secure authentication and API security solutions using OAuth2, OpenID Connect, JWT, and RBAC
- Strong system design and scalable architecture capability
- Experience with CI/CD pipelines, testing frameworks, version control, and agile delivery methodologies
Nice to have
- Experience with Azure OpenAI, Azure AI Search, Azure Functions, Azure API Management, Azure Key Vault, and Azure Service Bus
- Familiarity with LangChain, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworks
- Experience with vector databases, embedding models, reranking, and grounding techniques
- Experience with Docker, Kubernetes, Terraform, or Infrastructure as Code practices
- Understanding of enterprise security, compliance, and governance frameworks
- Experience designing event-driven and serverless AI systems on Azure
Additional details
- Location: India
- Contract Duration: 12 Month Contract
- Work Type: Remote
- Frontend Tech Stack: React, TypeScript, Tailwind
- Backend Tech Stack: Python (FastAPI), .NET APIs
- AI Stack: Azure OpenAI, LangChain, Semantic Kernel, RAG Pipelines
- Data Tech Stack: PostgreSQL, Redis, Azure AI Search, Vector Databases
- Cloud & DevOps Tech Stack: Azure Functions, Azure API Management, GitHub Actions, Docker, Kubernetes, OpenTelemetry
- Originally posted on Himalayas