Were hiring a Senior AI Engineer to join a newly formed AI Engineering group dedicated exclusively to RIVO, our flagship SaaS platform transforming global trade finance.
This is a high-impact role in a lean team with a clear mission: deliver production-grade AI capabilities end-to-end, from shaping the solution and validating it quickly, to production rollout, monitoring, and continuous improvement. We are not experimenting with AI. We are embedding it directly into the product, and building the AI foundation and reusable infrastructure that will power RIVO for years to come.
If you are a senior backend engineer with strong hands-on experience building LLM-based systems in production, and you want to own meaningful AI solutions inside a global SaaS product, this role is for you
Location: Kfar Saba, Israel
Reporting to: AI Team Lead
Roles and Responsibilities
Lead the design, development, and deployment of AI-powered services and product features into production.
Design and build scalable and reliable backend infrastructure to support AI capabilities (APIs, workflows, guardrails, monitoring, cost controls).
Own the lifecycle of AI services end-to-end: discovery, prototyping, evaluation, production rollout, monitoring, iteration, and maintenance.
Contribute to building RIVOs AI foundation by developing reusable building blocks (shared libraries, templates, integration patterns, evaluation utilities).
Apply advanced prompt engineering techniques and LLM orchestration patterns (tool/function calling, structured outputs, routing, fallback strategies) to achieve reliable and predictable behavior.
Implement and optimize retrieval-based systems including embeddings, vector search, and RAG pipelines.
Research, evaluate, and recommend models, tools, and frameworks, balancing quality, latency, cost, and maintainability.
Write high-quality, production-ready code and actively participate in code reviews and architectural discussions.
This is a high-impact role in a lean team with a clear mission: deliver production-grade AI capabilities end-to-end, from shaping the solution and validating it quickly, to production rollout, monitoring, and continuous improvement. We are not experimenting with AI. We are embedding it directly into the product, and building the AI foundation and reusable infrastructure that will power RIVO for years to come.
If you are a senior backend engineer with strong hands-on experience building LLM-based systems in production, and you want to own meaningful AI solutions inside a global SaaS product, this role is for you
Location: Kfar Saba, Israel
Reporting to: AI Team Lead
Roles and Responsibilities
Lead the design, development, and deployment of AI-powered services and product features into production.
Design and build scalable and reliable backend infrastructure to support AI capabilities (APIs, workflows, guardrails, monitoring, cost controls).
Own the lifecycle of AI services end-to-end: discovery, prototyping, evaluation, production rollout, monitoring, iteration, and maintenance.
Contribute to building RIVOs AI foundation by developing reusable building blocks (shared libraries, templates, integration patterns, evaluation utilities).
Apply advanced prompt engineering techniques and LLM orchestration patterns (tool/function calling, structured outputs, routing, fallback strategies) to achieve reliable and predictable behavior.
Implement and optimize retrieval-based systems including embeddings, vector search, and RAG pipelines.
Research, evaluate, and recommend models, tools, and frameworks, balancing quality, latency, cost, and maintainability.
Write high-quality, production-ready code and actively participate in code reviews and architectural discussions.
Requirements:
7+ years of software development experience, with at least 3 years focused on AI/LLM-based applications.
Proven experience delivering AI capabilities into production environments and maintaining them over time.
Deep understanding of LLMs and their practical application to real-world problems (e.g., OpenAI, Anthropic, Mistral, open-source).
Extensive experience with Python and/or Node.js for backend development in distributed systems.
Strong grasp of prompt design, embeddings, and AI API orchestration.
Experience with evaluating AI systems (offline evaluation, regression tests, monitoring, analytics).
Advantages:
Experience working with cloud providers (AWS preferred) and modern engineering tools (CI/CD, containerization, infrastructure-as-code).
Familiarity with vector databases (pgvector, Pinecone, Weaviate, Qdrant, OpenSearch).
Solid understanding of RAG pipelines, reranking, hybrid retrieval techniques, and optimization strategies.
Experience integrating open-source models or model-serving approaches (e.g., vLLM, llama.cpp, quantization, self-hosting).
Skills
Strong ownership and accountability, comfortable delivering independently and driving tasks to completion.
Ability to operate in a global, multi-cultural environment and collaborate across time zones.
Strong organizational and time management skills.
Ability to prioritize tasks effectively and balance speed with quality.
Strong work ethic, proactive, self-motivated, and results-driven.
Excellent communication and collaboration skills.
Proficient in spoken and written English
7+ years of software development experience, with at least 3 years focused on AI/LLM-based applications.
Proven experience delivering AI capabilities into production environments and maintaining them over time.
Deep understanding of LLMs and their practical application to real-world problems (e.g., OpenAI, Anthropic, Mistral, open-source).
Extensive experience with Python and/or Node.js for backend development in distributed systems.
Strong grasp of prompt design, embeddings, and AI API orchestration.
Experience with evaluating AI systems (offline evaluation, regression tests, monitoring, analytics).
Advantages:
Experience working with cloud providers (AWS preferred) and modern engineering tools (CI/CD, containerization, infrastructure-as-code).
Familiarity with vector databases (pgvector, Pinecone, Weaviate, Qdrant, OpenSearch).
Solid understanding of RAG pipelines, reranking, hybrid retrieval techniques, and optimization strategies.
Experience integrating open-source models or model-serving approaches (e.g., vLLM, llama.cpp, quantization, self-hosting).
Skills
Strong ownership and accountability, comfortable delivering independently and driving tasks to completion.
Ability to operate in a global, multi-cultural environment and collaborate across time zones.
Strong organizational and time management skills.
Ability to prioritize tasks effectively and balance speed with quality.
Strong work ethic, proactive, self-motivated, and results-driven.
Excellent communication and collaboration skills.
Proficient in spoken and written English
This position is open to all candidates.
