Multi-Agent systems jobs

Design, build, and maintain an AI agent platform and related infrastructure, support DevOps operations, and enable engineering teams to adopt AI technologies.

Responsibilities

Design, build, and maintain our AI agent platform, including multi-agent orchestration, tool integrations, context management, and agent execution.
Develop robust evaluation and testing frameworks for AI agents, including automated evals, regression testing, and quality monitoring.
Build observability for AI systems, covering execution tracing, reliability, latency, performance, and cost optimization.
Implement security and governance for agentic systems, including access controls, human-in-the-loop approvals, audit logging, and safe execution.
Build and maintain the infrastructure required to deploy, scale, and operate AI applications in production.

Skills

software engineering platform engineering DevOps LLM-powered applications AI agents multi-agent systems

AI Engineer - Forward Deployed Engineer

Traversal · Posted Nov 3, 2026

Open

New York, New York, United States
Full-time
$200K–$275K per year
3+ years

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Lead the design and implementation of scalable, robust backend systems to support AI agents and observability tools, prototype and evaluate prompting strategies, collaborate with researchers and product engineers, provide white glove deployment support, build long‑term customer relationships, and champion Traversal’s mission in the field.

Compensation

We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $200,000–$275,000, plus equity and benefits.

Responsibilities

Lead the design and implementation of scalable, robust backend systems to support AI agents and observability tools.
Prototype and evaluate prompting strategies, reasoning workflows, and tool‑use policies for agents operating on large‑scale observability data and complex troubleshooting workflows.
Collaborate with AI researchers, product engineers, and infrastructure teams to drive cross‑cutting upgrades to our core platform and product offerings.
Provide white glove deployment support for the Traversal platform and products in enterprise environments.
Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.

Requirements

Nice to have: communication
Nice to have: project management
Nice to have: infrastructure as code
Nice to have: SRE day‑to‑day workflows

Skills

Lead, AI Engineering (m/f/d)

Bain & Company · Posted Nov 5, 2026

Open

Paris, Île-de-France, France
3+ years

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Lead AI Engineer responsible for designing, building, and shipping generative AI systems and agentic solutions for Bain’s clients.

Responsibilities

Contribute to the design, development, and deployment of end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.
Build and iterate on multi-component AI pipelines such as Retrieval-Augmented Generation, fine-tuning, embedding generation, hybrid retrieval strategies, reasoning, tool use, and orchestration across AI workflows.
Build and contribute to agentic systems, applying sound engineering principles around separation of concerns, memory architecture, and tool integration.
Contribute across the full stack: model experimentation, evaluation design, and production system deployment.
Build and maintain APIs, microservices, CI/CD pipelines, and cloud-native deployments with attention to observability and reliability.

Requirements

Nice to have: French language proficiency at C1 level or higher
Nice to have: experience mentoring peers
Nice to have: experience with ReAct, RLAIF, and other HITL + feedback loops
Nice to have: experience with hybrid or graph-based retrieval approaches

Skills

software engineering

Principal AI Software Engineer

Palo Alto Networks · Posted Mar 30, 2026

Open

California, United States
On-site
Full-time · Principal
$236K–$323K per year
10+ years
Visa sponsorship

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Lead AI architecture and strategy for generative AI transformation within Palo Alto Networks’ internal and external business applications.

Compensation

$235,600.00 - $323,400.00/yr

Responsibilities

Architect AI gateway and unified API for LLMs
Design and implement observability pipelines for GenAI
Optimize cost and performance of LLM usage
Integrate guardrails for safety and compliance
Develop multi-agent systems and A2A workflows

Requirements

Bachelor’s degree in Computer Science or equivalent
Nice to have: Java
Nice to have: Node.js
Nice to have: AI tracing tools
Nice to have: LangSmith

Skills

Python Large Language Models Multi-Agent systems Agent-to-Agent communication Observability AI safety Guardrails

Ingénieur GenAI(F/H)

Thales Group · Posted Nov 5, 2026

Open

Tours, France +1 more
2+ years

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Locations (2)

Tours, France
Vélizy, France

Responsibilities

Expertise Agentique/IA/LLM auprès de nos clients
Développement d'agents à l'aide de framework type LangGraph/LangChain en Python
Implémentation de RAG dans des bases de connaissances
Construction de jumeaux numériques
Développement de cas d’usage métier

Requirements

Bachelor's degree in Computer Science

Skills

Python Julia Scala API creation multi-agent systems

Director, AI/ML

AstraZeneca · Posted Nov 9, 2026

Open

Bangalore, Karnataka, India
Hybrid
Full-time · Director
12+ years

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A senior individual-contributor role acting as the technical authority guiding advanced AI across the commercial landscape—from traditional ML to Generative and agentic AI.

Responsibilities

Define and drive the technical vision, roadmap and architecture for traditional ML, Generative AI and agentic AI capabilities
Provide hands-on technical leadership to project teams; set design direction, review architectures and code, remove blockers
Lead the design of multi-agent systems and LLM applications, including orchestration, tool use, memory, guardrails and human-in-the-loop patterns
Establish standards for evaluation, including automated and human-in-the-loop methods, benchmarking, and quality gates
Drive approaches to fine-tuning, distillation and reinforcement learning (including RL from feedback)

Requirements

computer science
mathematics
statistics
engineering
physics

Skills

Generative AI LLMs prompt engineering context engineering retrieval-augmented generation

GenAI Architect

Zensar · Posted Nov 9, 2026

Open

India
10+ years

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Lead the design and governance of enterprise-wide Generative AI architecture, defining strategy, standards, and best practices for scalable, secure, and responsible AI solutions across cloud-native environments.

Responsibilities

Define enterprise-wide Generative AI architecture strategy, standards, and best practices
Design scalable and secure LLM-powered solutions using Azure OpenAI and Azure AI Services
Architect enterprise-grade RAG platforms leveraging vector databases, semantic search, and knowledge management systems
Design and govern Agentic AI ecosystems utilizing AI Agents, tool calling, orchestration, and autonomous workflows
Evaluate and select appropriate foundation models, embeddings, and multimodal architectures

Requirements

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field
Nice to have: Microsoft Certified: Azure Solutions Architect Expert
Nice to have: Microsoft Certified: Azure AI Engineer Associate
Nice to have: Microsoft Certified: Azure AI Fundamentals
Nice to have: Experience working with Fortune 500 enterprise AI transformation programs

Skills

Generative AI & LLMs Large Language Models (LLMs)

Senior Full Stack Engineer – AI Agents & MCP

Travel Booster by Galor · Posted Nov 9, 2026

Open

Tel Aviv, Tel Aviv, Israel
Full-time · Senior
5+ years

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We are looking for an experienced Senior Full Stack Engineer to design and implement scalable, production-ready solutions and integrate modern technologies such as LLMs, MCP, and agent-based frameworks into our platforms.

Responsibilities

Develop APIs and microservices for integration with internal and external systems
Build and deploy AI-powered features using LLMs (OpenAI, Azure OpenAI, Hugging Face).
Implement MCP-based integrations for context-aware workflows.
Create and orchestrate AI agents for automation and intelligent decision-making.
Write production-grade code for AI workflows, including prompt engineering, function calling, and agent orchestration.

Requirements

Nice to have: Agile
Nice to have: Scrum

Skills

JavaScript TypeScript C#React Node.js REST APIs microservices

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