6 days ago
Cluj-Napoca, Romania or Timişoara, RomaniaSenior
Responsibilities
- Design, develop, and maintain end-to-end AI-powered applications using Python, React, and TypeScript.
- Build scalable backend services, REST APIs, front-end applications, enterprise integrations, and AI orchestration layers.
- Develop generative AI and agentic AI applications using LLMs, agent workflows, tool calling, memory, and human-in-the-loop patterns.
- Design and implement RAG pipelines involving document ingestion, chunking, embeddings, retrieval, reranking, and response generation.
- Integrate vector databases, search technologies, commercial and open-source LLMs, cloud services, and enterprise APIs.
- Implement LLM evaluation, tracing, monitoring, guardrails, logging, metrics, alerting, and other observability mechanisms.
- Deploy and operate secure, scalable applications using cloud platforms, Docker, Kubernetes, Terraform, and CI/CD pipelines.
- Write maintainable and testable code, perform unit, integration, API, and end-to-end testing, and conduct code reviews.
- Participate in architecture and technical design discussions, evaluate emerging AI technologies, and support other developers through mentoring and knowledge sharing.
- Own solutions from concept and prototyping through production deployment, monitoring, and continuous improvement.
Requirements
- Strong professional experience with Python, React, and TypeScript.
- Experience with FastAPI, Flask, Django, REST APIs, asynchronous programming, microservices, distributed systems, and API integration.
- Experience building modern front-end architectures with reusable components, state management, responsive interfaces, and API integration.
- Strong understanding of clean code, design patterns, testing, version control, and code review practices.
- Experience with relational or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis.
- Hands-on experience developing LLM-powered Generative AI and Agentic AI applications, including prompt engineering, tool/function calling, and structured outputs.
- Experience with LangChain, LangGraph, LlamaIndex, Haystack, RAG architectures, embeddings, semantic or vector search, retrieval, reranking, and vector databases.
- Understanding of LLM challenges including hallucinations, context limitations, prompt injection, latency, cost, security, and evaluation.
- Experience implementing LLM observability, evaluation, tracing, and guardrails; knowledge of LoRA and PEFT is advantageous.
- Hands-on experience with at least one of Microsoft Azure, AWS, or GCP, plus Docker, Kubernetes, CI/CD, Infrastructure as Code, and preferably Terraform.
- Understanding of DevOps, MLOps, LLMOps, AIOps, monitoring, logging, distributed tracing, and scalable, resilient production systems.
- Preferred experience with multi-agent workflows, Kafka, RabbitMQ, WebSockets, Server-Sent Events, OAuth 2.0, OpenID Connect, JWT, enterprise search, document processing, responsible AI, and AI security.
- Experience working directly with clients, translating business requirements into technical solutions, leading technical initiatives, mentoring developers, or contributing to architecture decisions is valued.
Benefits
- The posting highlights a fulfilling career, balanced lifestyle, diversity, and an inclusive workplace.
Tech Stack
Apache KafkaAWSAzureCSSDjangoDockerElasticsearchFastAPIFlaskGoogle Cloud PlatformHTMLKubernetesMongoDBMySQLNext.jsPostgreSQLPythonRabbitMQReactRedisTerraformTypeScript
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.