Responsible for designing and implementing specific architectural components and solutions for AI agents within the Bluefield framework, collaborating with Generative AI Engineers.
Compensation
Salary Range: $175,860.00 - $214,940.00
Responsibilities
Design detailed technical solutions and blueprints for individual AI agents, including data flows, API integrations, and component interactions.
Ensure agent development efforts strictly follow established architectural patterns, coding standards, security protocols, and best practices.
Optimize Google Agent Space and Google Cloud Platform services for agent performance, cost-efficiency, and scalability.
Design and contribute to the developpment of reusable agentic components, libraries, and common services.
Provide expert-level troubleshooting for complex architectural and integration challenges.
Requirements
Bachelor's degree in Computer Science
Data Science
related field, or equivalent practical experience
Nice to have: Healthcare payer domain
Nice to have: Solution Architect Associate certification
Design, build, and operate production-grade agentic AI systems combining foundation models, software services, enterprise data, tools, and automation.
Compensation
The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. – United States of America: Annual Salary USD 132,500 - 252,500 in Colorado // 143,000 - 290,500 in California // 126,500 - 290,500 in Georgia & North Carolina & Texas
Responsibilities
Design and develop scalable architectures for production-grade agentic AI systems.
Build agent orchestration, multi-agent workflows, state management, memory, tool integration, and human-in-the-loop capabilities.
Design reusable execution harnesses and services that separate AI reasoning and planning from deterministic execution.
Develop model-agnostic interfaces supporting multiple foundation models, providers, and inference platforms.
Build and integrate MCP servers, APIs, tool registries, skills, enterprise services, and data sources.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.
Nice to have: Cybersecurity automation
Nice to have: Security-sensitive systems
Nice to have: Open-weight models
Nice to have: Commercial foundation-model platforms
We are looking for an experienced GenAI Senior Engineer to design, build, and maintain scalable, secure, and production-grade AI platforms and applications.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $120,000-$150,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.
Responsibilities
Design, develop, and maintain scalable, secure, and highly available GenAI platforms and AI-powered applications on AWS.
Architect and implement Agentic AI solutions, multi-agent systems, tool integrations, function calling, and workflow orchestration frameworks.
Design and implement enterprise-grade RAG solutions using embeddings, vector databases, semantic search, reranking, and knowledge retrieval techniques.
Build AI applications leveraging Amazon Bedrock for LLM inference, model orchestration, prompt management, and foundation model integrations.
Develop reusable AI platform components, SDKs, APIs, accelerators, and reference architectures.
Lead Bosch’s NextGen AI initiative and drive enterprise-wide adoption of Generative AI and Agentic AI solutions.
Responsibilities
Define AI strategy, roadmap, governance principles, success metrics, and service offerings.
Own the end-to-end lifecycle of ChatGPT Enterprise and related AI services, from demand management and implementation to operations and continuous improvement.
Translate business requirements into secure, scalable, and compliant AI solutions.
Serve as the technical advisor for ChatGPT Enterprise and the broader NextGenAI ecosystem, providing solution design, integration guidance, and implementation support.
Collaborate with business stakeholders, architects, engineers, security, compliance, procurement, vendors, and executive leadership.
Design, build, and operate production-grade agentic AI systems that combine foundation models, software services, enterprise data, tools, and automation.
Compensation
The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. – United States of America: Annual Salary USD 132,500 - 252,500 in Colorado // 143,000 - 290,500 in California // 126,500 - 290,500 in Georgia & North Carolina & Texas
Responsibilities
Design and develop scalable architectures for production-grade agentic AI systems.
Build agent orchestration, multi-agent workflows, state management, memory, tool integration, and human-in-the-loop capabilities.
Design reusable execution harnesses and services that separate AI reasoning and planning from deterministic execution.
Develop model-agnostic interfaces supporting multiple foundation models, providers, and inference platforms.
Build and integrate MCP servers, APIs, tool registries, skills, enterprise services, and data sources.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.
Nice to have: Cybersecurity automation
Nice to have: Security-sensitive systems
Nice to have: Open-weight models
Nice to have: Commercial foundation-model platforms
Design, build, and operate production-grade agentic AI systems that combine foundation models, software services, enterprise data, tools, and automation.
Compensation
The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. – United States of America: Annual Salary USD 132,500 - 252,500 in Colorado // 143,000 - 290,500 in California // 126,500 - 290,500 in Georgia & North Carolina & Texas
Responsibilities
Design and develop scalable architectures for production-grade agentic AI systems.
Build agent orchestration, multi-agent workflows, state management, memory, tool integration, and human-in-the-loop capabilities.
Design reusable execution harnesses and services that separate AI reasoning and planning from deterministic execution.
Develop model-agnostic interfaces supporting multiple foundation models, providers, and inference platforms.
Build and integrate MCP servers, APIs, tool registries, skills, enterprise services, and data sources.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.
Nice to have: Cybersecurity automation
Nice to have: Security-sensitive systems
Nice to have: Open-weight models
Nice to have: Commercial foundation-model platforms
Lead enterprise-scale solution architecture for a cloud-native, IoT-enabled platform in the life sciences and clinical diagnostics industry.
Compensation
The expected base salary for this position ranges from $55.00 to $63.00/hour.
Responsibilities
Define and lead end-to-end architecture, technical roadmap, and modernization strategy
Design scalable, modular, cloud-native architecture across application, transport, and processing layers
Lead cloud and IoT architecture supporting device connectivity, real-time telemetry, instrument health monitoring, event processing, remote commands, software updates, and large-file transfers
Architect secure, reliable device communications for customer firewalls, restricted networks, intermittent connectivity, and air-gapped environments
Define data engineering and processing architecture, including ingestion pipelines, ETL, operational data stores, analytics, and event-driven processing
Requirements
Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related technical discipline
Grafana Labs is seeking a Staff Engineer (AI & Automation) to own the AI agent infrastructure and automation platform that powers our Marketing Operations organization. You’ll build multi-agent architectures, LLM integrations, and backend services that connect AI models to internal and third-party data platforms.
Compensation
In Canada, the base compensation range for this role is CAD 164,490 - CAD 197,389.
Responsibilities
Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation
Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP or similar)
Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps)
Implement observability and feedback loops including logging, performance metrics, prompt iteration, and cost management
Build MCP servers, APIs, and microservices connecting AI models to business systems (CRMs, email, calendars)
Solution Architect – Cloud, IoT & AI-Driven PlatformsComputer Task Group, Inc · Remote
Stage intégration d'agents IA au sein d'infrastructures réseau (F/H)Orange Business · Châtillon, France
Staff AI EngineerGrafana Labs · Remote, Canada