Multi Agent Systems

Multi Agent Systems Engineer Jobs

4 jobs found

2d ago

Senior AI Engineer

Diverse Lynx Aguadilla

Aguadilla

2d ago

$50 - $55/hr Contract Senior Agentic Ai AI

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Job Description

Diverse Lynx is seeking a Senior AI Engineer to lead the design, development, and deployment of agentic AI capabilities, with a focus on autonomous multi-agent systems. The role partners with business, data, and platform teams to deliver scalable, secure, production-grade AI platforms. This onsite contract position in Aguadilla, Puerto Rico offers an hourly rate of $50 to $55.

Responsibilities

Architect and implement Agentic AI systems, incorporating planning, reasoning, task execution, memory, and feedback loops.
Develop multi-agent architectures including task agents, reasoning agents, tool-calling agents, and orchestration agents.
Apply retrieval-augmented generation, Knowledge Graph, and memory-based AI patterns for enterprise use cases.
Integrate large language models with enterprise systems, APIs, tools, and workflows.
Define end-to-end AI solution architecture from data ingestion to inference and observability.
Build reusable AI services, agent frameworks, and orchestration layers.
Ensure AI solutions are scalable, resilient, performant, and secure.
Collaborate with cloud, data, and MLOps teams to productionize solutions.
Define agent evaluation metrics, including accuracy, autonomy, cost, latency, and safety.
Embed Responsible AI guardrails covering governance, explainability, auditability, and compliance.
Work with product owners, domain SMEs, and architects to translate business problems into AI solutions.
Mentor junior engineers and contribute to AI engineering standards and best practices.
Support client discussions, solution walkthroughs, and technical decision making.

Requirements

Strong proficiency in Python (mandatory).
Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, or equivalents.
Experience with large language models including OpenAI, Azure OpenAI, Anthropic, and open-source models.
Expertise in RAG, embeddings, vector databases, and prompt engineering.
Experience building multi-agent orchestration, tool calling, and workflow automation.
Experience with vector stores such as Pinecone, FAISS, Weaviate, Chroma, and similar technologies.
Knowledge of knowledge graphs, ontologies, and semantic search.
Cloud experience on Azure, AWS, or GCP.
Familiarity with APIs, microservices, and event-driven architectures.
Model monitoring, evaluation, and cost optimization.
8–12+ years of overall software or AI engineering experience.
3+ years hands-on experience in Generative AI and emerging Agentic AI systems.
Experience delivering production-grade AI solutions in enterprise environments.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.

Technologies

Python
LangGraph
LangChain
LlamaIndex
AutoGen
CrewAI
OpenAI
Azure OpenAI
Anthropic
Pinecone
FAISS
Weaviate
Chroma
Azure
AWS
GCP
APIs
Microservices
Event driven architectures
Knowledge Graph

Nice to Have

Experience in regulated industries such as pharma, healthcare, or life sciences.
Exposure to knowledge graphs, scientific/R&D workflows, or enterprise automation.

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4d ago

Machine Learning Engineer, Agentic Systems

ServiceNow Mountain View, CA

Mountain View, CA

4d ago

Full time Backend Developer Agent Orchestration Ai Workflows

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Job Description

This distributed systems engineering role builds the runtime infrastructure powering Moveworks AI agents in Mountain View, CA (onsite), focusing on orchestration, execution, and real-time delivery of agent responses rather than a traditional ML role.

Responsibilities

Agent orchestration engine: design and operate a state machine that manages long running agent sessions, coordinating planning, execution, and user interactions across multiple LLM calls and tool invocations
Distributed session management: enforce lease based ownership through DynamoDB conditional writes, maintain heartbeats, and enable crash recovery via checkpointing
Event driven messaging pipeline: leverage SQS FIFO for ordered delivery, process events with Kafka consumers, and stream in real time using gRPC and Socket.IO
Structured concurrency: use Python asyncio TaskGroups to run multiple concurrent tasks per session (polling messages, lease heartbeats, publishing outputs, orchestrator work) with fail fast semantics and clean cancellation
Observability: instrument with OpenTelemetry, propagate distributed trace context across async boundaries, and manage custom span lifecycles for minutes-long sessions
Caching and state management: Redis and DynamoDB key-value stores scoped per organization and per bot, optimize batch reads, and support hot reload of configuration

Requirements

Distributed systems: experience with consistency models, idempotency, exactly once delivery, and distributed locking or leasing
Concurrent and async programming: strong skills in Python asyncio or Go goroutines, with structured concurrency and cancellation handling
Event driven architectures: familiarity with message queues (SQS, Kafka), pub/sub patterns, backpressure, and delivery guarantees
Database systems for infrastructure: DynamoDB (conditional writes, transactions) and Redis (connection pooling, pub/sub)
Observability: OpenTelemetry, distributed tracing, span context propagation, and Prometheus metrics
gRPC and protobuf: streaming RPCs, service interface design, and common error handling patterns
2+ years building production backend or infrastructure systems
Strong in Python or Go, ideally both
Experience designing and operating systems that handle real traffic at scale
Comfort with ambiguity and solving novel problems without standard solutions

Technologies

Python
Go
asyncio
DynamoDB
Redis
SQS
Kafka
gRPC
protobuf
Socket.IO
OpenTelemetry
Prometheus

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5d ago

Staff Machine Learning Engineer, Agentic Systems

ServiceNow Mountain View, CA

Mountain View, CA

5d ago

Full time Agent Orchestration Agentic Ai Ai Agents

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Job Description

Staff Machine Learning Engineer on the agent lab team in Mountain View, CA, focusing on scalable AI agents, memory, orchestration, and end-to-end integration with Moveworks and ServiceNow.

Responsibilities

Tackle difficult engineering challenges to design and evolve reliable, capable AI agent systems at scale.
Develop and productionize cutting edge AI algorithms and architectures for scalable deployment.
Leverage current machine learning, large language models, and AI agents to improve products and deliver compelling user experiences.
Influence the product roadmap and steer the evolution of engineering domains to deliver enduring value for customers.
Write robust, extensible, readable, and high performance code.
Collaborate with ML, security, product, user experience, and customer success experts to learn from one another and deliver a leading enterprise AI product.
Mentor teammates on building, maintaining, and evolving high quality software.
Collaborate with ML engineers to share knowledge and build world class AI systems.

Requirements

8+ years designing, building, and improving production systems, preferably at scale.
Clear analytical and communication skills for complex engineering problems and systems.
Comfort with giving and receiving feedback, and maintaining high operational standards for yourself and teammates.
Ready to operate in a Mac development environment, with proficiency in Python, Go, and/or Java.
Willingness to ship quickly in a startup setting with a high degree of ownership.
Meticulous attention to detail.
Motivation to deliver product improvements using production‑grade code.
Proven appetite for rapid, incremental wins and completing challenging projects efficiently.
Curiosity about adjacent engineering disciplines and a commitment to staying at the forefront of applied AI.

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9d ago

Lead Machine Learning Engineer - Generative AI and Agent Platforms

JPMorganChase Jersey City, NJ

Jersey City, NJ

9d ago

$164k - $260k/yr Full time Ai Ml Ai Platform Artificial Intelligence

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Job Description

JPMorgan Chase offers a competitive total rewards package designed to support your growth and well being. This onsite Jersey City opportunity centers on building and operating production grade AI agents and agent platforms for payments technology, applying enterprise scale MLOps across the platform and business units.

Benefits

Base salary
Health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching
Commission-based pay and/or discretionary incentive compensation (cash and/or forfeitable equity)

Responsibilities

Design and deliver production ready AI agents across a federated portfolio, guiding solutions from prototype through launch and ongoing operations
Engineer reliable retrieval systems for production use, including hybrid retrieval-augmented generation patterns with vector search and graph-based retrieval where appropriate, plus robust chunking, ranking, and grounding
Implement memory patterns for agents, covering episodic and semantic memory with recall, summarization, and decay policies aligned to use-case needs
Assemble entitlement-aware and tenant-aware context so agents reason only over permitted data, enabling traceability and auditability
Orchestrate multi-agent workflows and integrate external tools and data sources through secure connectors and standardized interfaces
Develop evaluation frameworks spanning task-level and end-to-end assessments, regression suites, automated scoring, and release gates for quality and safety
Deploy and operate agent services on public cloud platforms such as AWS and/or Azure, applying rigorous software development lifecycle, security, resiliency, and observability practices
Improve runtime performance and reliability by instrumenting tracing, monitoring, and incident-response playbooks for agent services
Collaborate with product and business leaders to translate use cases into shipped capabilities, define success metrics, and drive improvements from production feedback

Requirements

Formal training or certification in applied AI and machine learning concepts with 5+ years of applied experience
Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience
Minimum 7 years of software development experience, including at least 4 years delivering AI or ML solutions
Hands-on experience building large language model–powered or agentic applications in production, including tracing, evaluations, and safety guardrails
Strong programming skills in Python with solid fundamentals in data structures, algorithms, and applied statistics
Practical experience with retrieval-augmented generation, embedding strategies, retrieval quality measurement, and vector databases
Proficiency operating production workloads in AWS, Azure, or Kubernetes
Experience designing data models and building systems using SQL and NoSQL technologies for real-time or near real-time use cases
Strong communication skills and ability to partner effectively with senior technical and business stakeholders

Technologies

Databricks
GenAI Gateway
Amazon Web Services
Microsoft Azure
Kubernetes
Python
Vector databases
Go
Rust
JavaScript
TypeScript
Graph databases
SQL
NoSQL

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Multi Agent Systems Engineer Jobs

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Machine Learning Engineer, Agentic Systems

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