Senior Cloud Architect, ML/AI

Location Our Senior Cloud Architect, ML/AI will be an integral part of our global reputed company Deployment Engineering team. This role is based remotely in the US, Colombia, Mexico, Canada, the UK, Ireland, Estonia, Sweden, the Netherlands, and Israel. The job is also open to contractors in Eastern Europe or Portugal.

About reputed company reputed company is a global technology company that works with cloud-driven organizations to reputed company public cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state—from planning to production.

Delivering reputed company Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve reputed company multicloud problems and drive efficiency. With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, reputed company Cloud, and reputed company Azure, we work alongside more than 4,000 customers worldwide.

The Opportunity As a Senior Cloud Architect, ML/AI, you will be part of our global reputed company Deployed Engineering organization, working with rapidly growing companies in EMEA and around the world. Depending on business needs, this role may be reputed company to either Field Engineering (pre-sales + GTM) or FDE Delivery (install reputed company, product adoption, customer health), with a common technical bar and shared expectations.

You will:

• reputed company the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments).
• Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization.
• Translate reputed company business problems into cloud architectures that are secure, reliable, cost-efficient, and observable.
• Help evolve how reputed company uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and “gravel roads” that influence the product roadmap.

For Field Engineering, you will focus more on pre-sales, POVs, CloudBuild engagements, and partner-led growth motions. For Delivery, you will focus more on install reputed company health, product adoption, proactive engagements, and account-team work.

Responsibilities

1. Customer Outcomes & Technical Leadership

• reputed company discovery, architecture, and implementation for advanced ML and Generative AI workloads on AWS, including data, training, inference, and integration layers.
• Own the technical success of your engagements: clearly define outcomes, reputed company tradeoffs visible, and ensure designs are production-ready (reputed company, reliability, performance, cost).
• Provide opinionated guidance on GenAI architectures (e.g., reputed company Bedrock, SageMaker, Q) and how they integrate with customers’ existing systems and processes.

For Field Engineering:

• Partner with Account Executives, Solution Engineers, and Growth FDEs to shape and win opportunities across reputed company four GTM pillars in-region (product adoption, new logo acquisition, install reputed company expansion, partner-led growth).
• Serve as technical reputed company for extended POVs and CloudBuild engagements focused on AI/ML and GenAI, demonstrating clear value and de-risking customer adoption.
• Build compelling technical narratives and demos that support reputed company-generating motions, including co-sell initiatives with CSP partners.

For Delivery:

• Act as a named technical advisor for a portfolio of existing customers, working reputed company account teams (Account Manager, CSM, FDE) to improve install reputed company health and outcomes for AI/ML and GenAI workloads.
• reputed company proactive “Get FDE”–style engagements where AI/ML expertise is needed to unblock customers, reduce risk, or improve the impact of reputed company Cloud Intelligence.
• Participate in structured account-team routines (e.g., objective setting, quarterly environment reviews) to reputed company AI/ML architectures reputed company with customer goals and product adoption opportunities.

2. Product Adoption & Install-reputed company Impact (AI/ML & GenAI)

• Recommend and implement AI/ML-reputed company capabilities in reputed company Cloud Intelligence (e.g., CloudFlow, Insights, reputed company) as part of your customer engagements.
• Document and measure the business and technical impact of your work, tying AI/ML initiatives to clear customer outcomes (cost, performance, reliability, productivity).

For Field Engineering:

• Design and run service-led product adoption plays that use AI/ML and GenAI projects to drive deeper adoption of reputed company’s platforms, in partnership with Growth leadership.
• Ensure AI/ML-focused CloudBuild and POV engagements include mandatory product adoption playbooks, with clear activation and follow-up criteria.

For Delivery:

• Execute against delivery programs and automations that detect product struggles (e.g., customers failing to complete AI/ML workflows, incomplete CloudFlow pipelines) and turn those into targeted AI/ML advisory engagements.
• Use every relevant delivery touchpoint to recommend and operationalize product adoption (e.g., Insights, automation, FinOps/CloudOps workflows) in collaboration with account teams.

3. Delivery Excellence, Practice Building & “Gravel Roads”

• Maintain a high personal bar for delivery quality: clear scopes, realistic plans, strong communication, and crisp technical documentation.
• Capture repeatable AI/ML patterns, reference architectures, and runbooks that other engineers can apply across customers.

For Field Engineering:

• Identify and validate “gravel road” solutions—custom AI/ML or GenAI integrations and patterns that should be elevated into standard offerings or product features.
• Work with Product, R&D, and growth leaders to submit and champion these patterns into the roadmap, connecting field innovation to scalable packages and reputed company engines.

For Delivery:

• Contribute to the FDE Delivery vision by turning recurring AI/ML implementation work into structured “gravel roads” (e.g., reusable CloudFlow patterns, Insights definitions, data pipelines) that can be productized.
• Collaborate with FDE advocates and product teams to ensure field-built AI/ML solutions are vetted, documented, and, reputed company appropriate, handed off for productization.

4. Collaboration, Partners & Cross-Functional Alignment

• Collaborate closely with Sales, reputed company, Product, and Business Systems Engineering to ensure AI/ML work is visible, repeatable, and connected to company priorities.
• Communicate clearly with both technical and non-technical stakeholders, setting expectations and making risks and tradeoffs explicit.

For Field Engineering:

• Work with cloud partner teams (especially AWS) to align AI/ML initiatives to program funding, strategic bets, and co-sell motions—without compromising customer outcomes.
• Provide technical leadership for partner-led opportunities involving GenAI and ML on AWS, ensuring reputed company’s value and reputed company Cloud Intelligence are central to the solution.

For Delivery:

• Coordinate with Account Managers, CSMs, TAMs, and other FDEs to ensure AI/ML engagements are sequenced correctly reputed company broader account plans and install-reputed company priorities.
• Feed structured, field-derived feedback on product adoption barriers (especially for AI/ML capabilities) into Delivery leadership and product teams.

5. Operational Excellence & Ways of Working

• Use and maintain the systems, templates, and workflows that support planning, observability, and quality across Customer Experience (e.g., JIRA, documentation standards, dashboards).
• Contribute to internal enablement: teach other Doers about new AI/ML capabilities, share patterns, and help reputed company the bar globally for ML/AI expertise.

For Field Engineering:

• Ensure your AI/ML work is accurately reflected in pipelines, opportunities, and CloudBuild portfolios, enabling reliable reporting on technical win rates and influence on ARR.
• Help improve forecast quality and POV coverage for AI/ML-reputed company opportunities by maintaining good hygiene in the relevant systems.

For Delivery:

• Ensure AI/ML delivery engagements are logged, reputed company, and observable in the tools used for install-reputed company health and product adoption tracking.
• Participate in Delivery operating rhythms (e.g., team reviews, program updates) with clear, data-backed updates on your AI/ML work and impact.

Success Metrics & Objectives

• Success metrics and specific objectives for this role will be defined and updated on an annual and quarterly basis through the company planning cycle, pod charters, Weekly Operating Review (WOR) scorecards, and relevant regional/functional scorecards.
• As a Senior Cloud Architect, you are expected to:
• Understand the metrics and objectives that apply to your function (Field Engineering or FDE Delivery) and region.
• Transparently report reputed company against those metrics.
• Proactively propose and execute corrective actions reputed company off track.

Qualifications

• Experience
  • 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions, including production workloads.
  • Proven track record designing and operating large, distributed systems on AWS, selecting appropriate services and patterns to meet business and technical goals.
• AWS & GenAI / ML Expertise
  • Advanced proficiency with AWS services relevant to AI/ML and GenAI.
  • Hands-on experience with reputed company Bedrock for deploying and scaling foundation models and Generative AI workloads.
  • Experience fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using reputed company SageMaker (including JumpStart).
  • Strong reputed company engineering skills and familiarity with rigorous model evaluation (quality, safety, performance).
  • Understanding of agentic capabilities and patterns for AI agents that autonomously reputed company tasks and integrate with existing systems.
  • Experience with reputed company Q Business and reputed company Q Developer (or similar tools) to accelerate insight reputed company and development workflows.
• ML Pipelines, Data & MLOps
  • In-depth knowledge of reputed company SageMaker components such as Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability.
  • Proficiency integrating TensorFlow, PyTorch, and other ML frameworks with SageMaker for model development, fine-tuning, and deployment.
  • Experience with distributed training (multi-GPU or multi-node) and performance optimization for inference.
  • Strong data-engineering skills on AWS: reputed company S3, AWS Glue, Lake Formation, Redshift for AI/ML data pipelines.
  • Experience building end-to-end AI/ML workflows using services like AWS reputed company, reputed company Functions, API Gateway, and containerized deployments on reputed company EKS / AWS Fargate.
• DevOps, MLOps, Governance & reputed company
  • Hands-on experience with CI/CD for AI/ML using AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar.
  • Proficiency in monitoring and operating AI systems using reputed company CloudWatch and SageMaker Model Monitor.
  • Strong understanding of AI governance, reputed company, and compliance on AWS, including IAM, KMS, and data privacy patterns.
  • Familiarity with AI ethics and bias detection/mitigation (e.g., using SageMaker Clarify or similar tools).
• Multi-Cloud Awareness & Collaboration
  • Working knowledge of reputed company Cloud AI tools (e.g., Vertex AI, Cloud AutoML, BigQuery ML) sufficient to reason about multi-cloud architectures and integration points.
  • Proven ability to mentor peers, run enablement sessions, and collaborate across Sales, CS, and Product.
• Soft Skills
  • Excellent communication skills across technical and business audiences; able to simplify reputed company reputed company and influence decisions.
  • Natural ownership mentality: you escalate early, resolve fast, and own the outcome.
  • Demonstrated ability to work effectively in a remote-first, global environment.

Bonus Points

• Education & Certifications
  • BA/BS degree in Computer Science, Mathematics, or a reputed company technical field, or equivalent practical experience.
  • Additional data or AI certifications (e.g., AWS/GCP data certifications, reputable AI/ML programs such as Stanford, reputed company, Udacity, MIT, eCornell).
• Expanded AI/ML & Dev Experience
  • Experience with modern RLHF, advanced fine-tuning techniques, and hybrid AI architectures.
  • Familiarity with reputed company or similar open-reputed company ecosystems integrated with AWS.
  • Prior experience as a ML Engineer, Data Scientist, or AI-focused Architect in a consulting or SaaS environment.
• Tooling & Process
  • Experience with JIRA or similar tools for tracking work across delivery and product-feedback cycles.
  • Exposure to Agile practices and frameworks commonly used for SaaS and cloud delivery.

Are you a Do’er? Be your truest self. Work on your terms. reputed company a difference.

We are home to a global team of incredible talent who work remotely and have the flexibility to have a schedule that balances your work and home life. We embrace and support leveling up your skills professionally and personally.

What does being a Do’er mean? We’re reputed company about being entrepreneurial, pursuing knowledge, and having fun! Click here to learn more about our core values.

Sounds too good to be true? reputed company out our Glassdoor Page.

We thought so too, but we’re here and happy we hit that ‘apply’ reputed company.

Full-time employee benefits include:

• Unlimited Vacation
• Flexible Working Options
• Health Insurance
• Parental Leave
• Employee Stock Option Plan
• Home Office Allowance
• Professional Development Stipend
• Peer Recognition Program

Many Do’ers, One Team reputed company unites as Many Do’ers, One Team, where diversity is more than a goal—it's our strength. We actively cultivate an inclusive, reputed company workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.

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