Tieto
We are seeking a skilled AI Engineer to design, build, and deploy AI-powered applications and intelligent systems for global clients.
Company: Tieto
Role: AI Engineer
Location: Bangalore, India
Role Focus: • Design and develop AI-powered applications using LLMs and modern AI frameworks • Build and optimize RAG pipelines for enterprise use cases • Develop agentic AI systems with multi-agent orchestration • Implement basic retrieval evaluation: relevance scoring, top-k result quality, and pipeline latency benchmarking • Build tool-use integrations for AI agents: REST API connectors, database query tools, file system tools, and enterprise system adapters • Write and maintain agent evaluation test suites: unit tests for tool calls, integration tests for agent workflows, and regression tests against eval datasets • Integrate AI models with APIs, backend systems, and enterprise applications • Perform data preprocessing, feature engineering, and model evaluation • Develop REST APIs and microservices for AI applications • Deploy models on cloud environments (AWS/Azure/GCP) • Collaborate with cross-functional teams to deliver AI solutions for global customers • Develop and maintain AI application layers: chat interfaces, document processing pipelines, semantic search, and AI-assisted workflow automation • Implement multi-agent orchestration using LangGraph, AutoGen, CrewAI, or Semantic Kernel • Investigate and resolve production incidents in AI systems: trace agent call chains, identify failure modes, and implement fixes • Implement and maintain PII detection and redaction controls within AI pipelines • Monitor model performance and improve system efficiency
AI/LLM-based application development, LLMs: GPT, Gemini, Claude, Agentic AI systems, LangChain, LangGraph, CrewAI, RAG pipelines and embeddings, Sentiment Analysis, Topic Modeling, Q&A Chatbots, Text Classification, APIs and web apps, Flask, FastAPI, Streamlit, SQL skills, databases, PostgreSQL, Snowflake, Pinecone, ChromaDB, FAISS, cloud platform, AWS / Azure / GCP, model deployment and monitoring
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