[Hiring] Principal Software Engineer @Nomura Holdings, inc.

Role Description

Wholesale Core Services Software Engineering is the engineering enablement division responsible for creating the platforms, SDKs, frameworks, tools, and standards that accelerate software delivery across the Wholesale business. The division solves systemic engineering challenges by improving developer productivity, simplifying technology adoption, standardizing software engineering practices, and enabling teams to build secure, scalable, resilient, and high-quality services efficiently.

Key Responsibilities

• Design, develop and manage scalable applications using Java, Spring Boot, and Python.
• Develop distributed systems with advanced microservices patterns.
• Create applications on Kubernetes clusters with comprehensive container orchestration.
• Implement AI-powered features using Large Language Models (LLMs) and agentic AI workflows.
• Develop autonomous AI agents with multi-step reasoning, tool usage, and decision-making capabilities.
• Build multi-agent systems with agent orchestration, communication protocols, and collaborative workflows.
• Implement agentic workflows including planning, execution, reflection, and self-correction mechanisms.
• Optimize RAG (Retrieval Augmented Generation) pipelines integrated with agentic systems.
• Utilize vector databases for efficient similarity search and document retrieval.
• Develop embedding systems for text and data processing.
• Integrate AI agents with external tools and APIs for enhanced functionality and automation.
• Practice Test-Driven Development (TDD) with comprehensive unit, integration, and contract testing.
• Apply DevOps and platform engineering principles including infrastructure as code, automated deployments, and monitoring.
• Design and implement efficient data ingestion and processing pipelines.
• Collaborate with cross-functional teams to deliver intelligent software solutions.
• Participate in code reviews and contribute to technical documentation.
• Optimize application performance and troubleshoot production issues in distributed environments.

Qualifications

• Core Expertise in Python, Java, and Spring Boot with microservices development.
• Strong experience with Micro-service Architecture & Event-driven architecture.
• Experience in distributed systems design and implementation.
• Strong knowledge of SQL and NoSQL databases.
• Proficiency in Test-Driven Development (TDD) and various test integration frameworks.
• DevOps/Platform Engineering skills including CI/CD, infrastructure automation, and monitoring.
• Kubernetes proficiency including deployment, scaling, and service mesh technologies.

AI/ML Expertise

• Advanced Python development skills, including experience with frameworks like LangChain, LangGraph, or similar LLM frameworks.
• Familiarity with Hugging Face transformers.
• Experience with vector databases (Qdrant, Weaviate, or similar).
• Knowledge of embedding models (OpenAI, BERT, or similar).
• Experience with agent frameworks: LangGraph, AutoGen, or custom agent implementations.
• Understanding of multi-agent systems: agent communication, coordination, task delegation, and collaborative problem-solving.
• Experience with agentic workflows: planning agents, execution agents, reflection mechanisms, and self-correction loops.
• Knowledge of agent memory systems: short-term and long-term memory, conversation history, and context management.
• Experience with tool integration: API calling, database queries, file operations, and external service interactions.
• Familiarity with agent orchestration: workflow management, state machines, and conditional execution paths.
• Understanding of core RAG components: document chunking, embedding generation, vector similarity search, and LLM prompt engineering.
• Knowledge of advanced patterns: multi-query RAG, hybrid retrieval (BM25 + Neural Search), parent-child chunking, and query decomposition.
• Experience with pipeline optimization techniques: text splitters, embedding integration, vector store operations, query routing, and response synthesis.
• Knowledge of enhancement techniques: auto-merging chunks, semantic routing, context optimization, re-ranking mechanisms, and multi-vector retrieval.
• Experience with agentic RAG: integration of RAG systems with autonomous agents for dynamic information retrieval and processing.

Benefits

• Competitive salary and benefits package.
• Remote work flexibility.
• Professional development opportunities.
• Access to cutting-edge AI technologies and resources.
• Collaborative and innovative work environment.
• Health insurance.
• Annual performance bonus.
• Regular team events and activities.
• Training in emerging AI technologies, agentic systems, and distributed systems patterns.