AI Solutions Architect Jobs

Discover the latest remote and onsite AI Solutions Architect roles across top active AI companies. Updated hourly.

Check out 448 new AI Solutions Architect opportunities posted on The Homebase

Forward Deployed Engineer - Paris

New
Top rated
Aircall
Full-time
Full-time
Posted

Lead customer discovery and design sessions to map business processes, identify automation opportunities, and define solution architecture. Design, build, and deploy integrations using low/no-code platforms (Zapier, Make, n8n, Workato) and CRM automation tools (HubSpot Workflows, Salesforce Flow) with API connectors. Collaborate with Engineering to validate technical feasibility, resolve blockers, and share field learnings that inform product improvements. Configure and optimize the AI Agent by defining intents, prompts, actions, guardrails, and performance metrics. Manage complex, cross-functional deployments by defining timelines, aligning stakeholders, ensuring accountability, and delivering on time and within scope. Create scalable models and reusable frameworks such as templates, playbooks, and reference architectures to expedite future projects. Champion continuous learning and enablement through training peers, running internal workshops, and documenting best practices to raise the technical bar across the team. Run global, targeted outbound campaigns within the existing customer base to generate pipeline and accelerate adoption, working closely with the customer marketing team. Collaborate with GTM leadership to embed routines and cadences that drive accountability for new product pipeline, forecast accuracy, and performance tracking. Own regional top-line targets for assigned products by collaborating with AEs and AMs who hold add-on quotas. Act as an internal product owner within the GTM function by defining product-specific MRR strategies, coordinating cross-functional support, and ensuring delivery of the AI-enabled communication platform. Collaborate with Product and PMM to shape the AI Voice Agent roadmap based on customer needs, integration insights, and field learnings. Drive internal and external product education including enablement for System Integrators and channel partners. Maintain deep awareness of AI and CX industry trends to keep Aircall's positioning competitive and feed insights back into product and GTM strategies.

Undisclosed

()

Paris, France
Maybe global
Onsite

Forward Deployed Engineer - Berlin

New
Top rated
Aircall
Full-time
Full-time
Posted

Lead customer discovery and design sessions to map business processes, identify automation opportunities, and define solution architecture. Design, build, and deploy integrations using low/no-code platforms (Zapier, Make, n8n, Workato) and CRM automation tools (HubSpot Workflows, Salesforce Flow) with API connectors. Collaborate with Engineering to validate technical feasibility, resolve blockers, and share field learnings that inform product improvements. Configure and optimize the AI Agent defining intents, prompts, actions, guardrails, and performance metrics. Manage complex, cross-functional deployments by defining timelines, aligning stakeholders, ensuring accountability, and delivering on time and within scope. Create scalable models and reusable frameworks (templates, playbooks, reference architectures) that make future projects faster and more consistent. Champion continuous learning and enablement by training peers, running internal workshops, and documenting best practices to raise the technical bar across the team. Run global, targeted outbound campaigns within the existing customer base to generate pipeline and accelerate adoption, working closely with the customer marketing team. Collaborate with GTM leadership to embed routines and cadences that drive accountability for new product pipeline, forecast accuracy, and performance tracking. Own regional top-line targets for assigned products by collaborating with Account Executives and Account Managers who hold add-on quotas. Act as an internal product owner within the GTM function by defining product-specific MRR strategies, coordinating cross-functional support, and ensuring Aircall delivers the leading AI-enabled communication platform. Collaborate with Product and PMM to shape the AI Voice Agent roadmap based on customer needs, integration insights, and field learnings. Drive internal and external product education, including enablement for System Integrators and channel partners. Maintain deep awareness of AI and CX industry trends, ensuring Aircall's positioning remains competitive and insights continuously feed back into product and GTM strategies.

Undisclosed

()

Berlin, Germany
Maybe global
Onsite

Staff Backend Solution Architect Engineer

New
Top rated
Heidi Health
Full-time
Full-time
Posted

Architect and build backend services that power LLM-based agents and clinical automations. Design robust APIs and data models that are secure, observable, and extensible for other teams. Optimize performance and cost by profiling hot paths, tuning databases, and right-sizing cloud resources. Automate quality by writing unit and integration tests, crafting alerts, and owning on-call runbooks to ensure trust in every interaction. Partner with product, AI, and front-end engineers to ship new capabilities from concept to production within weeks.

Undisclosed

()

Sydney or Melbourne, Australia
Maybe global
Remote

AI Solution Architect

New
Top rated
Arize AI
Full-time
Full-time
Posted

The role involves debugging and fixing issues in the Arize platform and shipping pull requests with the fixes, building internal tools and copilots powered by generative AI to enhance the team’s capabilities, rapidly prototyping proof-of-concepts for customer use cases, and working collaboratively across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.

Undisclosed

()

Buenos Aires
Maybe global
Remote

Partner Solutions Architect, Applied AI

New
Top rated
LangChain
Full-time
Full-time
Posted

The role involves partnering with cloud providers, system integrators, and ISVs to design and build agentic AI solutions, creating production ready solutions, sample repositories, and reference architectures using LangChain, LangGraph, and LangSmith. The person will collaborate closely with product and engineering teams to support partner integrations and solution design. They will enable partners through technical workshops, solution walkthroughs, and hands on collaboration, and gather partner and customer feedback to translate it into actionable insights for product and integration roadmaps.

$170,000 – $200,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Solutions Architect

New
Top rated
Cohere
Full-time
Full-time
Posted

As a Solutions Architect at Cohere, you will develop and deliver advanced agentic AI solutions using Cohere's foundation models and Agentic AI Foundry - North. You are responsible for architecting scalable, secure, and customizable NLP and generative AI solutions tailored to enterprise customer needs. The role involves collaborating with customers to understand complex workflows, designing pilots, and translating business requirements into technical solutions that include model fine-tuning, custom agents, and agent orchestration. You will support the deployment and integration of large language models (LLMs) and custom solutions into production environments using Kubernetes, Docker, and cloud infrastructures, ensuring high performance and security. You will lead technical engagements such as deep dives into AI architectures, workshop facilitation, and establishing best practices for agent-based AI systems and model customization. Additionally, you will work with product development to provide customer feedback on agentic AI capabilities, contribute to product enhancements, and help shape future features.

Undisclosed

()

San Francisco, United States
Maybe global
Remote

Forward Deployed Engineer

New
Top rated
Notable
Full-time
Full-time
Posted

As a Forward Deployed Engineer, you will partner directly with customers to understand their biggest challenges and rapidly design, implement, and integrate technical solutions that drive real impact. You will leverage engineering expertise to design scalable AI workflows for clinical and operational use cases, producing professional-grade systems and data-flow diagrams defining interfaces, failure modes, and integration points with EHRs and legacy systems. You will build and deploy Large Language Model (LLM) powered workflows, applying advanced prompting strategies, building agentic workflows, and tuning vector stores for quality, latency, and cost. You will perform technical validation of AI algorithm outputs and ensure strict adherence to HIPAA/SOC 2 controls, establishing guardrails such as audit trails and least-privilege access for safe clinical deployment. You will independently manage technical implementation plans, defining scope and setting expectations with customers, driving prototypes into production and facilitating the transition to steady-state ownership alongside Customer Success teams. You will serve as the technical voice in customer meetings, translating complex platform capabilities into clear value propositions for executives and non-technical stakeholders. Additionally, you will provide input to internal cross-functional teams on platform gaps to help widen competitive advantage.

$160,000 – $185,000
Undisclosed
YEAR

(USD)

San Mateo, United States
Maybe global
Hybrid

Forward Deployed Engineer - Strategist

New
Top rated
ElevenLabs
Full-time
Full-time
Posted

As a Forward Deployed Engineer Strategist, responsibilities include meeting with strategic customers to understand their critical audio and voice AI needs and identify their biggest pain points, identifying relevant use cases through deep engagement with customer problems and workflows, and working with Engineers to implement voice and audio AI technology into innovative solutions. Design and architect bespoke integrations for customers to ensure the technology fits seamlessly into their products and operations. Guide customers on best practices for implementing voice and audio AI models to maximize effectiveness. Present results of work and proposals for future work to audiences ranging from technical teams to C-suite executives. Collaborate with Research and Product teams to incorporate field insights into ElevenLabs' software products and AI models. Build and deliver compelling demos of the voice and audio AI technology to new and existing customers. Scope out potential applications in new industries and expand AI solutions across different sectors globally. Take full ownership of end-to-end execution of major projects for strategic partners, working hands-on to deliver high-impact solutions. Collaborate daily with customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.

Undisclosed

()

Maybe global
Remote

Forward Deployed Engineer

New
Top rated
Reka
Full-time
Full-time
Posted

As a Forward Deployed Engineer, you will lead technical discovery with customers to understand their business challenges, data environment, infrastructure landscape, and operational workflows. You will architect end-to-end multimodal agentic AI solutions involving LLMs, vision models, speech models, RAG pipelines, realtime perception–decision–action loops, agent frameworks, planning, tool-use, orchestration, and integration with enterprise APIs, databases, security systems, VMS, IoT, MDM, or existing apps. You will conduct PoCs, benchmarks, and A/B evaluations, producing clear documentation on metrics, model performance, constraints, and ROI. You will work closely with customer data teams to gather, clean, and preprocess multimodal datasets including text, images, audio, video, and sensor data, and build and optimize custom LLM prompts, fine-tuned LLM/vision models, domain-specific embedding models, custom scorers, loss functions, and evaluation metrics. You will advise customers on LLMOps best practices including lifecycle management, scalable APIs, agent reliability, function-calling strategies, and safety guardrails. You will demonstrate how Reka’s multimodal models can interpret CCTV, documents, screens, emails, speech, and logs, combine perception with reasoning and action, and integrate with enterprise tools to perform tasks autonomously. You will help customers understand advanced concepts such as tool-use and planning, multi-agent workflows, knowledge grounding and retrieval, chain-of-thought versus distilled reasoning, and observability and telemetry for AI agents. You will design and run workshops for audiences from business leaders to data scientists and train customers on AI fundamentals, multimodal models, deployment patterns, and Reka platform usage including APIs, SDKs, and agent creation. You will produce sample notebooks, reference architectures, code snippets, reusable templates, and best-practice guidelines. Internally, you will collaborate with product, engineering, and research teams to influence the roadmap based on customer needs, contribute internal prototypes, demos, agent frameworks or tools that improve presales velocity, and assist in competitive analysis against other AI vendors.

Undisclosed

()

Maybe global
Hybrid

Senior Software Engineer, Agentic Applications

New
Top rated
Databricks
Full-time
Full-time
Posted

Guide the technical evaluation phase for customers as a presales solutions architect, working hands-on to deliver and integrate Databricks' platform for big data, analytics, and AI solutions. Work with customers and the sales team to provide architectural guidance, develop demo applications, reference architectures, and support adoption and optimization of Databricks within enterprise ecosystems.

Undisclosed

()

Maybe global
On-site

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[{"question":"What does an AI Solutions Architect do?","answer":"AI Solutions Architects design comprehensive AI solutions that align with business goals. They evaluate organizational challenges, identify AI opportunities, and translate business problems into technical requirements. Their responsibilities include defining architectural patterns, conducting feasibility studies, and overseeing integration with existing systems. They collaborate with data scientists, engineers, and business stakeholders while providing technical leadership throughout the development lifecycle. AI Solutions Architects create documentation, implementation roadmaps, and architecture diagrams while ensuring compliance with ethical standards and regulations. They also monitor industry trends and mentor development teams on best practices for AI implementation."},{"question":"What skills are required for AI Solutions Architect jobs?","answer":"Strong technical expertise in AI/ML technologies is essential, including deep learning, NLP, computer vision, and generative AI models. Proficiency with cloud platforms like AWS SageMaker, Azure AI Services, or Google Vertex AI is typically required. Communication skills are crucial for explaining complex concepts to diverse stakeholders. Problem-solving abilities help identify where AI can address business challenges. Architecture design experience enables creating scalable, maintainable systems. Knowledge of data technologies (databases, data warehouses, streaming platforms) is needed for effective implementation. Project management capabilities help coordinate cross-functional teams. Understanding ethical considerations and regulatory compliance rounds out the necessary skillset."},{"question":"What qualifications are needed for AI Solutions Architect jobs?","answer":"Most employers require a bachelor's degree in computer science, data science, or related technical field, with many preferring master's degrees. Typically, 5+ years of experience in technical consulting, solutions architecture, or similar customer-facing roles is expected. Hands-on experience designing and implementing enterprise-level AI solutions is essential. Knowledge of machine learning model development and deployment is required. Industry certifications from cloud providers (AWS, Azure, GCP) specific to AI services strengthen applications. Experience leading cross-functional teams on complex projects is valuable. Demonstrated success with AI integration in existing enterprise environments is often a key qualification."},{"question":"What is the salary range for AI Solutions Architect jobs?","answer":"Salary for AI Solutions Architects varies based on several factors. Geographic location significantly impacts compensation, with technology hubs typically offering higher salaries. Years of experience, particularly with enterprise-level AI implementations, increases earning potential. Industry sector affects pay scales, with finance and technology often offering premium compensation. Specialized expertise in high-demand areas like generative AI or computer vision can command higher salaries. Organization size and resources influence package structures. Additional compensation often includes bonuses, equity, and benefits. The breadth of technical skills across cloud platforms, data technologies, and AI frameworks also impacts overall compensation."},{"question":"How long does it take to get hired as an AI Solutions Architect?","answer":"The hiring process for AI Solutions Architects typically takes 1-3 months. Initial screening often includes portfolio reviews of previous AI architectures and solutions. Technical interviews assess cloud platform knowledge, AI implementation experience, and architecture design skills. Many employers include case studies where candidates design solutions for specific business problems. Leadership assessment evaluates ability to guide cross-functional teams. Final rounds may involve presenting architecture proposals to senior stakeholders. Candidates with demonstrated experience in enterprise AI implementations, strong communication skills, and relevant technical certifications typically move through the process more quickly."},{"question":"Are AI Solutions Architect jobs in demand?","answer":"AI Solutions Architect roles show strong demand across industries as organizations implement enterprise AI strategies. Major firms like EY, OpenAI, and Sutter Health are actively recruiting for these positions. The role appears prominently in job forecasts for 2025-2026, particularly as generative AI deployment accelerates. Organizations need specialists who can bridge technical AI capabilities with business requirements while ensuring proper integration with existing systems. The specialized nature of AI architecture—combining machine learning expertise, enterprise architecture experience, and business acumen—creates significant demand for qualified professionals who can lead successful implementations. This demand spans multiple sectors including healthcare, finance, and technology."},{"question":"What is the difference between AI Solutions Architect and Traditional Solutions Architect?","answer":"AI Solutions Architects specialize in machine learning technologies, model development, and AI-specific deployment considerations that traditional Solutions Architects may lack. They understand unique infrastructure requirements for training and inference workloads. Traditional Solutions Architects focus on general enterprise applications, databases, and network configurations without specialized AI knowledge. AI architects must address ethical considerations, bias mitigation, and regulatory compliance specific to AI systems. They require deeper understanding of data processing pipelines and statistical modeling. Traditional architects typically work with more established technologies and integration patterns. AI Solutions Architects often collaborate more closely with data scientists and ML engineers, while traditional architects primarily work with software developers and DevOps teams."}]