- Location
- Bengaluru, Karnataka, India
- Job type
- Full-time
Required skills
- LangChain
- Python
- Azure
- backend
- FastAPI
- Java
- Kubernetes
- microservices
- REST APIs
About the role
Happiest Minds Technologies
Website:
happiestminds.com
Job details:
****8+ Years experience****
- Possess strong foundational knowledge in Java and Python, with solid problem-solving skills and a proactive attitude toward learning and adapting to new technologies.
- Design and develop Agentic AI systems capable of reasoning, planning, and executing complex workflows using Large Language Models.
- Build AI-powered services using LLM APIs such as OpenAI, Azure OpenAI Service, or other foundation model providers.
- Develop and orchestrate AI agents using frameworks such as LangChain, LangGraph, and LlamaIndex.
- Design and implement multi-agent systems, including agent collaboration, task decomposition, and tool usage.
- Build Retrieval-Augmented Generation (RAG) pipelines integrating enterprise knowledge sources.
- Integrate vector databases such as PgVector, Pinecone, Weaviate, or Milvus to enable semantic search and knowledge retrieval.
- Build scalable backend services using Java (Spring Boot / Netflix DGS) for enterprise integrations and high-throughput APIs.
- Write Python services using Object-Oriented design principles to support LLM orchestration, prompt engineering, and agent execution.
- Develop AI microservices using FastAPI to expose agent capabilities and LLM-powered workflows.
- Integrate AI agents with enterprise systems via REST APIs, event streams, and databases.
- Design and implement tool integrations enabling AI agents to interact with internal services, APIs, and automation workflows.
- Implement memory architectures for AI agents including short-term memory, long-term knowledge retrieval, and context management.
- Design observability, monitoring, and evaluation frameworks to measure LLM performance, agent behaviour, hallucination rates, and task success.
- Optimize prompt engineering, model selection, token usage, latency, and cost efficiency.
- Build guardrails and safety mechanisms for reliable AI system behaviour.
- Design, develop, and deploy AI services on Microsoft Azure, leveraging services such as Azure OpenAI, Azure Functions, Azure Kubernetes Service (AKS), and related cloud services.
- Design and run evaluation pipelines and experimentation frameworks to continuously improve AI agent accuracy, reliability, and performance.
- Collaborate with product managers and engineering teams to translate business problems into AI-driven solutions.
Gen AI
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