KaaIoT is the company behind the popular Kaa IoT Platform. It has been in broad use in nearly all major digitalized industries, and has been highly acclaimed in media and among IoT technology observers. Now we stand at the new milestone for our IoT product line while also expanding our expertise in emerging, cutting-edge technology.
31 серпня 2026

Senior Software Engineer (7+ years) — AI Agents & Search (вакансія неактивна)

віддалено

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

  • Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
  • Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
  • Integrate multiple LLM/model providers with secure configuration and graceful degradation
  • Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
  • Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team’s production-support model
  • Investigate incidents, drive root-cause analysis, and ship durable fixes
  • Design for permissions, tool approvals, multi-tenancy, and customer-data governance
  • Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

  • B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
  • 7+ years of relevant experience, or equivalent demonstrated senior-level impact
  • Strong Java software engineering skills
  • Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
  • Solid background in distributed systems, microservices, cloud services, or data-intensive backends
  • Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
  • Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
  • Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
  • SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
  • Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
  • Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
  • English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
  • Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

  • LangChain4j or similar agent frameworks
  • Python for AI services, evaluation harnesses, or sandboxed execution
  • React and TypeScript
  • gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
  • Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
  • AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
  • OpenSearch operations: index lifecycle management, relevance tuning, incident response
  • Open-source contributions

Details

  • Engagement: Long-term contract
  • Location: Europe (EU / EEA / UK), remote
  • Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team