AI Engineer

We are seeking a talented and experienced AI Engineer with a background in Data Science, Machine Learning, Backend development, or equivalent to join our professional services team of over 60 engineers, headquartered in Israel. The position is available full-time. This remote-first role focuses on Generative AI, specifically working with advanced Large Language Models (LLMs) and building AI agents. You'll work with state-of-the-art foundation models through platforms like AWS Bedrock and GCP Vertex AI to develop innovative GenAI applications and scalable AI infrastructure for our clients.

The Mission

At Opsfleet, we don't just "wrap" LLMs; we build autonomous, production-grade agentic systems. We are seeking an Engineer who understands that the future of AI isn't a single prompt, but a complex, stateful ecosystem of collaborating agents. You will be responsible for designing the cognitive architectures that allow multiple agents to negotiate, self-correct, and execute complex workflows in production.

Core Responsibilities

• Agentic System Design: Architect and deploy complex Multi-Agent Systems (MAS) that move beyond basic RAG into autonomous reasoning, planning, and execution.
• Context Orchestration: Design and implement dynamic Context Management strategies, including sliding windows, semantic summarization, and token-efficient pruning to maintain long-term coherence without exceeding model limits.
• Tool-Use & API Synthesis: Expertise in Function Calling and Tool Definition; specifically creating standardized interfaces using MCP for agents to interact with external APIs, databases, and local environments.
• Orchestration & Frameworks: You will be responsible for designing and implementing robust state-handling for long-running agentic tasks using LangChain, LangGraph, Agno, Strands, ADK, etc.
• Safety & Guardrails: Design and implement Production Safety Measures, including output sanitization, hallucination triggers, and autonomous circuit breakers to ensure reliability in high-stakes environments.
• Memory & Personalization: Build sophisticated memory layers that manage User Preferences and historical context, ensuring agents provide personalized, context-aware interactions over time.
• System Evaluations: Define and implement rigorous requirements for Agentic Evaluation, benchmarking trajectory consistency, tool-calling accuracy, and reasoning logic.

Technical Stack & Requirements

• Software Design: 5+ years of Python experience with a focus on Modular Architecture and clean code principles.
• Agentic Frameworks: Expert-level proficiency in modern orchestration frameworks (LangChain, LangGraph, Agno, Strands, ADK, etc.).
• Cloud Infrastructure: Deep experience with AWS Bedrock or GCP Vertex AI for enterprise-scale model deployment and agent hosting.
• Communication Standards: Hands-on experience with MCP for connecting agents to diverse data sources and tools, and A2A for cross-agent collaboration.
• Vector & Graph Databases: Proficiency in using Knowledge Graphs and vector storage to ground agentic reasoning and provide structured organizational memory.

Preferred Qualifications

• Agent Engine Mastery: Direct experience working with AgentCore architectures and native Agent Engines (AWS Bedrock Agents / GCP Vertex AI Agent Engine).
• Multi-Modal Expertise: Experience building agents capable of synthesizing information across Text, Vision, and Video sources.
• The "Agentic Mindset": You can explain the difference between a linear chain and a directed acyclic graph (DAG), and you know exactly when an agent is the right tool vs. a simple workflow.
• The Reviewer’s Eye: Experience conducting deep technical reviews of AI implementations, identifying architectural bottlenecks or "lazy" agent logic.
• Production Battle Scars: You’ve dealt with agents getting stuck in infinite loops or hallucinating tool-calls, and you know how to build the infrastructure to prevent it.

Why Opsfleet?

• Define Agentic Autonomy: You aren't just following tutorials; you are architecting the blueprint for how autonomous systems reason, collaborate, and execute. You will set the industry standards for agentic maturity, moving beyond simple task-execution into complex, self-correcting cognitive architectures.
• Complex Projects: Work on everything from internal coding agents to massive client-facing multi-agent orchestrators.
• Remote-First: A culture built by engineers, for engineers

Employment: Full-time position (40 hours/week)

Benefits: • Potential career paths • Collaborative remote team environment • Opportunity to contribute to open-source GenAI initiatives and research publications