Senior AI/ML Engineer (Multi-Agent Systems) Job at Orbis Consultants

Senior Machine Learning Engineer, Agentic

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Bellevue; Menlo Park; New York; Washington; Denver; Westlake; Chicago; Lake Mary; Clearwater; Gainesville

Salary:

146000.00 - 220000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

Strong technical expertise in software development, with understanding of agentic workflows—including reasoning loops, tool invocation, memory, and orchestration of autonomous AI agents
Hands-on experience using Large Language Models, including prompt engineering, fine-tuning, model distillation, and deploying optimized models (e.g. via DPO, PPO) into production environments
Proven ability to build and scale ML/AI systems, from experimentation to deployment—owning dataset generation, evaluation pipelines, A/B testing, and performance monitoring
Leadership and mentorship capabilities, with a track record of guiding complex technical projects and supporting the growth of teammates through code/design reviews and technical direction
Excellent communication and collaboration skills, with the ability to translate technical ideas into actionable plans and work effectively with cross-functional partners, including product and infrastructure teams
Innovation mindset and commitment to continuous learning and a bias toward action, staying at the forefront of ML/AI trends, agentic systems research, and best practices in tooling, safety, and evaluation

Job Responsibility

Design and create tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead
Build platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains
Develop feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior
Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling to improve agent performance
Launch and support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring
Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems

What we offer

Market competitive and pay equity-focused compensation structure
100% paid health insurance for employees with 90% coverage for dependents
Annual lifestyle wallet for personal wellness, learning and development, and more
Lifetime maximum benefit for family forming and fertility benefits
Dedicated mental health support for employees and eligible dependents
Generous time away including company holidays, paid time off, sick time, parental leave, and more
Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits
Bonus opportunities
Equity

Fulltime

Senior Agentic AI Developer

Senior Agentic AI Developer to build production-grade autonomous agents and orch...

Location

United States , San Francisco

Salary:

156000.00 - 234000.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

6+ years in software engineering, with 3+ years hands-on building production-grade AI/ML systems
Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain)
Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration
Strong Python/TypeScript skills and experience in microservices and distributed infrastructure
Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines
Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation
Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery
Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP)
Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques
Strong understanding of agent safety, bias mitigation, transparency, and ethical design practices

Job Responsibility

Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition
Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes
Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures
Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem
Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP)
Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows
Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles
Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall
Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement
Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems

What we offer

Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year
Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere
Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together
Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits
Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being
Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow
Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups
Community Engagement: Make a difference through our volunteering program

Fulltime

Senior Agentic AI Developer

Build production-grade autonomous agents and orchestration systems that reshape ...

Location

Argentina , Buenos Aires

Salary:

Not provided

GoFundMe

Expiration Date

Until further notice

Requirements

6+ years in software engineering
3+ years hands-on building production-grade AI/ML systems
Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain)
Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration
Strong Python/TypeScript skills and experience in microservices and distributed infrastructure
Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines
Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation
Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery
Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP)
Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques

Job Responsibility

Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition
Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes
Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures
Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem
Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP)
Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows
Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles
Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall
Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement
Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems

What we offer

Competitive pay
Comprehensive healthcare benefits
Financial assistance for things like hybrid work, family planning
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs

Senior Staff Software Engineer - AI

GEICO is seeking an experienced Engineer with a passion for building high-perfor...

Location

United States , Seattle, WA; Austin, TX; Palo Alto, CA; Chicago, IL; Dallas, TX

Salary:

110000.00 - 230000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

Experience building and deploying ML systems in production with cross-functional engineering teams
Fluency in at least two modern languages such as Python, Go, Java, C++, or C# including object-oriented design
Experience architecting multi-component ML platforms using open-source/cloud-agnostic components: Datastores: PostgreSQL, NoSQL (MongoDB, Cassandra, CosmosDB) Streaming: Kafka, Flink, or Spark Streaming
Experience with end-to-end ML lifecycle: version control, CI/CD, Kubernetes, testing, monitoring, and production support
Experience with cloud providers (Azure, AWS or GCP) in production ML environments
Experience with observability tools and distributed systems monitoring, logging, tracing, and root cause analysis
Experience building multi-agent systems using LLMs and agentic frameworks (e.g., LangChain, LangGraph, AutoGen, Semantic Kernel, CrewAI)
Hands-on experience with RAG, semantic search, and vector databases (e.g., Milvus, pgvector, Qdrant, ElasticSearch)
Experience designing human-in-the-loop workflows and safety controls for autonomous systems
Strong architecture and design skills with ability to influence technical direction and roadmap

Job Responsibility

Design and build a multi-agent AI platform where specialized agents autonomously detect, diagnose, and resolve issues through agent-to-agent (A2A) collaboration
Develop intelligent agents using LLMs and agentic frameworks that coordinate detection, diagnostic, remediation, and knowledge tasks with minimal human intervention
Define agent interaction protocols, A2A communication standards, and evaluation frameworks for agent decision quality and autonomous action safety
Architect vector database solutions (Milvus, pgvector, Qdrant) for semantic search and RAG to enable context-aware agent decision-making
Build end-to-end ML pipelines for severity classification, anomaly detection, failure pattern recognition, and impact forecasting using observability data
Establish scalable orchestration infrastructure for multi-agent workflows with CI/CD, automated evaluation, canary releases, and rollback strategies
Implement monitoring for agent interactions, A2A communication patterns, decision quality, data drift, and system reliability
Lead technical architecture ensuring scalability, observability, and integration with existing alerting, logging, and monitoring systems
Define standards for agent safety, explainability, governance, and human-in-the-loop controls for high-impact automated actions
Partner with SRE, Product, and Engineering teams to translate reliability goals into measurable ML objectives and maintain pragmatic technical roadmaps

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

Senior AI Engineer

HPE Galway are seeking a highly skilled Senior AI Engineer to join our growing A...

Location

Ireland , Galway

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, AI/ML or related technology
Minimum of 8+ years of work experience in cloud based and/or open source software development
3+ years of experience in AI/ML engineering with a focus on LLMs and knowledge retrieval systems
Strong hands-on experience with LLM frameworks: LangChain, LangGraph, PydanticAI, or similar
Proven experience implementing RAG systems and vector databases (PostgreSQL with pgvector, Pinecone, FAISS, Weaviate, Chroma)
Proficiency in Python with deep knowledge of ML libraries (PyTorch, TensorFlow, Transformers)
Experience with Model Context Protocol (MCP) server development and deployment
Understanding of Google ADK and A2A protocol implementations
Strong knowledge of cloud platforms (AWS, Azure, GCP) and their AI/ML services
Experience with prompt engineering, fine-tuning, and LLM optimization techniques

Job Responsibility

Design and develop AI-driven applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), and Graph RAG architectures
Implement and optimize RAG techniques for improved knowledge retrieval and contextual reasoning
Build and maintain graph-based AI solutions using modern frameworks like LangGraph, PydanticAI, and LangChain
Develop and deploy Model Context Protocol (MCP) servers for seamless data integration across various sources
Design scalable vector database solutions using Pinecone, Weaviate, or similar technologies
Integrate Google Agent Development Kit (ADK) and Agent-to-Agent (A2A) protocols for multi-agent workflows
Collaborate with cross-functional teams to translate business requirements into technical AI solutions
Maintain high code quality standards and implement comprehensive testing strategies

What we offer

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Fulltime

Senior AI Software Engineer

AnaVation is seeking a Senior Agentic-AI Software engineer to join our team that...

Location

United States , Chantilly

Salary:

Not provided

AnaVation

Expiration Date

Until further notice

Requirements

Active TS/SCI clearance within last 24 months
BA/BS in Computer Science or related field
BS + 10 Yrs or MS + 8 Yrs experience in computer science, AI, Machine Learning, or related field
5+ years of experience in AI/ML development
At least 2 years focused on Agentic AI or autonomous systems
Proven track record of deploying production-grade AI systems
Strong problem-solving skills
Ability to work in a fast-paced, collaborative environment

Job Responsibility

Design, develop, and deploy advanced Agentic AI systems that autonomously perform complex tasks, make decisions, and interact with dynamic environments
Collaborate with cross-functional teams to deliver scalable, efficient, and ethical AI solutions
Architect and implement agentic AI systems capable of autonomous decision-making, task planning, and execution
Design and integrate multi-agent systems to solve complex problems
Develop and fine-tune large language models (LLMs) and reinforcement learning (RL) models
Implement robust APIs and interfaces to integrate AI agents with external systems
Optimize AI models for performance, scalability, and low-latency inference
Conduct rigorous testing, validation, and monitoring of AI agents
Collaborate with product managers, data scientists, and software engineers
Stay updated on latest advancements in Agentic AI, LLMs, and RL

What we offer

Generous cost sharing for medical insurance for employee and dependents
100% company paid dental insurance for employees and dependents
100% company paid long-term and short term disability insurance
100% company paid vision insurance for employees and dependents
401k plan with generous match and 100% immediate vesting
Competitive Pay
Generous paid leave and holiday package
Tuition and training reimbursement
Life and AD&D Insurance

Fulltime

Senior AI Security Engineer

The Senior AI Security Engineer is a technical leader and engineering manager wi...

Location

Hungary , Budapest

Salary:

22713830.00 - 38083370.00 HUF / Month

Citi

Expiration Date

Until further notice

Requirements

8-10+ years of experience in software engineering, with demonstrable experience as a technical lead or engineering manager
Python mastery: Deep, hands-on experience building and maintaining production-grade Python applications and services
LLM engineering: Practical experience with LLM APIs (OpenAI, Anthropic, Google), prompt engineering, model evaluation, and input/output guardrails
Production systems: Track record of deploying and operating AI/ML systems in production at enterprise scale
Software engineering fundamentals: Clean code, design patterns, testable architecture, CI/CD, infrastructure-as-code
3+ years leading or managing engineering teams, including performance management, hiring, and career development
Track record of delivering complex software products in environments where priorities shift rapidly
Experience setting engineering standards and driving quality across a team's output
Demonstrated ability to mentor and develop engineers through code review, architectural guidance, and knowledge sharing
Proven capability to attract, develop, and retain engineering talent

Job Responsibility

Agentic AI Engineering & Use Case Incubation (40%): Own and evolve the Incubator Environment — the platform and tooling that enables CISO teams to move from idea to working PoC to validated use case
Partner with cybersecurity domain teams to understand their challenges, identify high-value AI use cases, and rapidly prototype agentic solutions
Design, build, and deploy agentic AI systems that autonomously perform cybersecurity tasks — including threat analysis, security control validation, intelligent triage, and response orchestration
Architect multi-agent orchestration systems, defining how AI agents collaborate, delegate, and escalate across security workflows
Implement robust agent infrastructure: tool use frameworks, memory and context management, planning/execution loops, guardrails, and human-in-the-loop controls
Build and maintain RAG pipelines, knowledge retrieval systems, and dynamic context assembly that underpin agent decision-making
Shepherd validated use cases through to production readiness and handoff to the dedicated product support team
Drive adoption and effective use of AI development tooling (Devin, GitHub Copilot, Claude Code) to maximize team velocity
Make key technical decisions on architecture, technology selection, and build-vs-integrate trade-offs
Incubator Platform & Technical Architecture (25%): Design and maintain the Incubator Environment architecture — a scalable, secure platform that enables rapid prototyping and validation of agentic AI use cases

What we offer

Cafeteria Program
Home Office Allowance (for colleagues working in hybrid work models)
Paid Parental Leave Program (maternity and paternity leave)
Private Medical Care Program and onsite medical rooms at our offices
Pension Plan Contribution to voluntary pension fund
Group Life Insurance
Employee Assistance Program
Access to a wide variety of learning and development programs, online course libraries and upskilling platforms, such as Udemy and Degreed
Flexible work arrangements to support you in managing work - life balance
Career progression opportunities across geographies and business lines

Fulltime

Senior Backend Engineer - Employee AI

Join our dedicated, fast-paced experimentation and innovation unit, where you'll...

Location

Germany , Leipzig

Salary:

Not provided

Staffbase

Expiration Date

Until further notice

Requirements

6+ years of professional experience in backend software development
Strong proficiency in Golang and preferably Java/Kotlin
Proven experience integrating various AI/ML models into production backend systems
Practical experience with prompt engineering
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
Experience building backend systems designed for complex agentic workflows or long-running conversational states
Familiarity with foundational LLM concepts such as retrieval-augmented generation (RAG)
Practical experience developing or managing MCP servers (Managing Conversational Protocols)
Familiarity with Agent-to-Agent (A2A) communication protocols and multi-agent system design
Experience with event-driven architecture and message queues (e.g. Kafka)

Job Responsibility

Design, develop, and maintain scalable and fault-tolerant backend services that power our AI applications
Apply advanced prompt engineering techniques to optimize model performance, manage context windows, and ensure reliable, high-quality responses
Implement model integration patterns to connect and orchestrate various external and internal services
Develop Agent-to-Agent (A2A) protocol communication strategies for complex multi-agent architectures
Implement systems for Managing Conversational Protocols (MCP servers) and Agent-to-Agent (A2A) protocol to handle and maintain long-running, stateful interactions
Define and implement observability standards for AI applications, including metrics for latency, cost, token usage, drift, and user-perceived quality
Implement logging, tracing, and monitoring tools to quickly diagnose and troubleshoot issues in the end-to-end AI pipeline
Collaborate with ML Scientists and Data Scientists to transition prototypes and models into production-ready, high-availability services
Ensure the security, reliability, and performance of all production systems
Participate in code reviews, architectural discussions, and technical strategy planning

What we offer

Competitive Compensation - we offer attractive salary packages including LTIP (Long Term Incentive Plan)
Flexibility - we offer flexible working time models and the option of hybrid work, and support this with a yearly flex work allowance of €1560
Recharge - with 31 vacation days annually (incl. one floating holiday), plus pro rata fully paid Fridays off during August
Wellbeing - Monthly Wellbeing Allowance €35, from fitness to mental health, hobbies to relaxation
Support - we’re offering a company pension scheme
Volunteers Day - you’ll get one day off per year for supporting a social project

Senior AI/ML Engineer (Multi-Agent Systems)

Orbis Consultants

Location:
European Union

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
April 05, 2026

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