לוח משרות דרושים AI Engineer בשרון

We are seeking an experienced, hands-on Senior AI Engineer to join the Generative AI applications Platform group and lead the backend implementation and architecture of AI/LLM solutions - from agent graphs and tooling to RAG, streaming, and production deployment.
As a Senior ML Engineer you will
Design and own agent architectures - Build and evolve graph-based agent workflows (multi-node LLM flows, tool execution, routing, human-in-the-loop review gates) using LangGraph, with clear state schemas, checkpointing, and streaming to production.
Turn product and user needs into backend AI - Work with Engineers, Product, and Analysts to translate business problems into technical requirements and implementations, including agent types, tools, RAG pipelines, and configuration-driven behavior.
Design, develop, and deploy GenAI capabilities end-to-end - LangChain tools and integrations, RAG (retrievers, vector stores, agentic flows), structured outputs, and APIs for chat, Copilot-style integrations, and MCP.
Raise the bar on quality and reliability - Establish patterns for observability (e.g., LangSmith), error handling, content safety, bounded autonomy (tool schemas, review workflows), and evaluation systems so that AI behavior is predictable and auditable.
Mentor and align the team - Provide technical guidance on LLM backend architecture and LangGraph/LangChain best practices so the team can iterate quickly and safely.

What We're Looking For
Role Overview: We are developing Ask our company - a high-load financial analysis system based on Large Language Models. The architecture is built on complex multi-agent orchestration using LangGraph, FastAPI, and Elasticsearch.
We are looking for a Senior Backend Engineer specialized in Generative AI to design agent workflows, optimize interactions with models (OpenAI, AWS Bedrock), and ensure the reliability of non-deterministic systems in production.
Tech Stack: Python (Asyncio), FastAPI, LangChain, LangGraph, Pydantic, Elasticsearch, AWS Bedrock / OpenAI API, LangSmith.
What You'll Do
Agent Architecture: Design and implement complex agent orchestration logic using LangGraph. You will define state management, conditional routing, and error handling within the agent graph.
Tool Engineering: Build and optimize the tool layer (function calling) that allows LLMs to interact with internal financial APIs and databases accurately.
Performance Optimization:
-Reduce end-to-end latency through asynchronous processing and streaming (SSE).
-Implement semantic caching strategies to minimize API costs and response time.
-Optimize token usage without sacrificing answer quality.
Observability & Evaluation: Implement automated evaluation pipelines using LangSmith. You will be responsible for setting up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment.
Advanced RAG: Refine retrieval strategies. Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion to feed the most relevant context to the model.

We are looking for an experienced and dynamic Team Lead to manage a talented group of frontend & backend engineers, qa testers and devops. In this role, you will oversee the design , development and delivery of versions of our software to our biggest customer, ensuring that it meets the highest standards of quality and efficiency.
Additionally, you will collaborate closely with stakeholders in the customer team and within the organization, requiring strong communication and leadership skills.
Key Responsibilities:
Lead, mentor, and manage a hybrid team (Onshore & Offshore) of 10 engineers (frontend, backend, quality, devops), fostering a collaborative and high-performance culture.
Oversee our AI-first transformation in your team- moving all coders to do 100% vibe coding
Collaborate with product owners, QA, DevOps, and other team members to deliver high-quality software solutions within an Agile framework.
Ensure the teams not only develop features but also write comprehensive automation tests to validate and cover their work, ensuring high quality and stability.
Ensure designs and implementations align with technical specifications, industry standards, and best practices.
Promote continuous improvement by exploring and adopting new technologies and methodologies.
Provide support for customer and delivery teams in successfully implementing projects based on the platform.
Contribute to all phases of the development lifecycle, from design through deployment to maintenance.
Write well-structured, testable, and efficient code when needed.