AI Solutions Engineer

2 days ago

Bengaluru, India Spigot Software Full time

Description : Requirements : - 2-5 years of professional experience in AI, Machine Learning, Data Science, and/or Automation roles.- Hands-on experience with developing and deploying AI solutions, with expert understanding of Generative AI concepts (e. g., LLMs, RAG architecture) and/or Agentic AI principles.- Proficiency in Python programming and experience with AI/ML libraries (e. g., LangChain, LlamaIndex, Hugging Face).- Familiarity with cloud-based AI/ML services (Azure OpenAI, GCP Vertex AI, or AWS Bedrock) and basic understanding of deployment processes.- Basic understanding of data pipelines and MLOps concepts.- Experience with prompt engineering and optimization techniques for LLMs.- Knowledge of vector databases (e. g., Pinecone, Weaviate, ChromaDB) for semantic search and retrieval.- Understanding of AI agent architectures including planning, reasoning, and tool-use capabilities.- Strong problem-solving skills and a keen interest in learning new technologies.- Good communication and teamwork skills with ability to translate technical concepts to non-technical stakeholders.- Experience with specific Generative AI frameworks or libraries (LangGraph, AutoGen, CrewAI, Semantic Kernel).- Exposure to building or working with multi-agent systems and agent orchestration patterns.- Familiarity with document understanding techniques, such as data extraction, OCR, or intelligent document processing (IDP).- Experience with fine-tuning or adapting foundation models for domain-specific tasks.- Knowledge of evaluation frameworks and metrics for LLM applications (e. g., RAGAS, human-in-the-loop evaluation).- Understanding of enterprise AI governance, responsible AI principles, and security best practices.- Experience implementing memory systems and context management for conversational AI.- Familiarity with streaming responses and real-time AI applications.- Experience using modern AI development tools (e. g., GitHub Copilot, Cursor) to enhance productivity.- Knowledge of function calling, tool integration, and API orchestration in agentic systems.- Experience with A/B testing and continuous improvement of AI systems.- Relevant coursework or certifications in AI/ML (e. g., Azure AI Engineer, AWS ML Speciality, Google Cloud ML Engineer).- Exposure to accounting, finance, or ERP systems for domain-specific AI applications. (ref:hirist.tech)

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