Skip to content
Cloud Engineer

The week's list

Every role like this one, in one letter

You are reading one posting. There are hundreds like it on the board, and new ones every week. Pick what you want, leave an email, and the list comes to you — no searching, no coming back here.

Counting what came out this past week…

The first letter arrives right away, then one a week. Unsubscribe in one click from any letter — the address goes nowhere else.

Cloud Engineer

FDE AI/ Solutions Architect (AI, Python/Data)

Provectus

Remote

Apply on the employer's site

Role description

Provectus is an
AWS Premier Partner
and an
Anthropic Strategic Partner
, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.

Our work centers on two verticals —
Financial Services & Insurance
and
Healthcare & Life Sciences
— where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.

Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.

Where this role sits
You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize:

  • Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction
  • Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered.

What You’ll Do:
Take the seat

  • Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
  • Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.

Build

  • Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases
  • Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
  • Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
  • Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
  • Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
  • Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.

Own the outcome.

  • Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number.
  • Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here.
  • Be credible with the customer’s engineers and their executives.
  • Shape what we commit to before we commit to it.

What You’ll Bring:
Mindset

  • Proactive and self-directed; identify problems before they're handed to you
  • Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job
  • B2+ English, comfortable collaborating across distributed, multicultural teams

Client Engagement

  • You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code
  • Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them
  • You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run

Technical depth

  • 7+ years building and running production systems.
  • Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes
  • Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks
  • Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
  • Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
  • Experience building and optimizing RAG systems in production
  • Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
  • Experience in making and defending architectural trade-off decisions
  • Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus
  • Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines
  • You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release
  • Model and agent monitoring, drift detection
  • Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs
  • Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus
  • MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus

Nice to have:

  • Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
  • Experience in one of the industries: financial services, insurance, healthcare
  • Consulting, professional services, or other embedded customer-facing delivery
  • A2A: you can explain agent-to-agent interoperability
  • AWS and Claude Code Certifications
  • CI/CD pipeline experience (GitHub Actions, GitLab CI)
  • Experience in an additional language (Go, TypeScript, or Rust)
  • Experience with Apache Spark, Apache Airflow, Kafkа

What We Offer:

  • The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
  • A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
  • A growing AI delivery practice where you help build the tooling and frameworks, not just use them
  • Remote-friendly culture
  • Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
  • Career growth; we actively develop our engineers
  • Access to the latest AI tools and premium subscriptions
  • Long-term B2B collaboration
  • Private medical insurance or a budget for your medical needs
  • Paid sick leave, vacation, and public holidays
  • Equipment and all the tech you need for comfortable, productive work

How we hire:

  • Intro conversation. The role, your background and aspirations, tech questions.
  • Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
  • HR Interview. Soft skills and expectations
  • HM interview. Tech questions; a live engineering session is also possible

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

Coming to this page

A resume for this role — and a ticket to the draw

We take the posting apart down to the real requirements and rewrite your resume against it — by asking, not inventing: no line appears without your confirmation. Sign in to get it first, and to enter the draw.

  • A resume for this exact role, not a universal one
  • Answers are kept: edit any one, not the whole conversation
  • All in your account — open it from any device

On the wheel

A discount on mentoring

Winners are drawn at random among entries with a confirmed email. The date and the full rules are on the draw page.

Draw rules

Cloud Engineer

Senior Infrastructure Engineer, AI/ML Systems

Portfolium (Acquired by Instructure)

Remotefulltime

Apply on the employer's site

Role description

At Instructure
, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.

We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:

Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.

This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build.

You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

What You'll Do

  • Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
  • Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
  • Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
  • Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
  • Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it

What You'll Need

  • Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
  • Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
  • Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
  • Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
  • Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
  • Comfort working through ambiguity and collaborating directly with data scientists and researchers

It Would Be a Bonus If You Had

  • Experience with ML platform components and data pipeline orchestration at scale
  • Experience running LLM-based or retrieval-based systems in production
  • Experience operating specialized data stores, including graph databases
  • Experience building internal tooling, templates, or reference implementations that other engineers adopted

Onsite Collaboration Requirement:
This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.

Why Join Us

Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.

At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.

We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.

Get in on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

  • Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
  • Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
  • Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
  • Comprehensive wellness programs and mental health support
  • Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
  • The technology and tools you need to do your best work
  • Motivosity employee recognition program
  • A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

Cloud Engineer

Senior Infrastructure Engineer, AI/ML Systems

Instructure

Remotefulltime

Apply on the employer's site

Role description

At Instructure
, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.

We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:

Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.

This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build.

You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

What You'll Do

  • Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
  • Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
  • Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
  • Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
  • Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it

What You'll Need

  • Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
  • Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
  • Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
  • Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
  • Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
  • Comfort working through ambiguity and collaborating directly with data scientists and researchers

It Would Be a Bonus If You Had

  • Experience with ML platform components and data pipeline orchestration at scale
  • Experience running LLM-based or retrieval-based systems in production
  • Experience operating specialized data stores, including graph databases
  • Experience building internal tooling, templates, or reference implementations that other engineers adopted

Onsite Collaboration Requirement:
This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.

Why Join Us

Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.

At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.

We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.

Get in on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

  • Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
  • Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
  • Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
  • Comprehensive wellness programs and mental health support
  • Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
  • The technology and tools you need to do your best work
  • Motivosity employee recognition program
  • A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

Cloud Engineer

Senior DevOps Engineer with Golang (f/m/x)

Sii Poland

Remote

Apply on the employer's site

Role description

We are looking for a skilled Senior DevOps Engineer to join a project focused on enhancing and modernizing client's cloud platform. This role offers the flexibility of remote work, allowing you to contribute to significant improvements in cloud infrastructure and automation processes. If you are passionate about cloud technologies and automation, this opportunity may be the right fit for you.

Your tasks

  • Building and maintaining platform integrations and automation workflows
  • Developing solutions using Go/Golang to enhance cloud operations
  • Implementing Infrastructure as Code using Terraform
  • Integrating cloud APIs for VMware, Azure, and AWS platforms
  • Creating and managing CI/CD pipelines to streamline deployments
  • Utilizing PowerShell and Bash scripting for automation
  • Managing Kubernetes and container platforms for efficient application deployment
  • Applying configuration management tools like Ansible to maintain system integrity

Requirements

  • Minimum 5 years of experience in DevOps or cloud engineering
  • Hands-on mastery of Go/Golang development
  • Experience with VMware and cloud API integrations
  • Knowledge of AWS or Azure services
  • Advanced level of English

Nice to have

  • Practical experience in Azure and/or AWS platform engineering
  • Familiarity with Ansible or similar configuration management tools
  • Strong command of Terraform and Infrastructure as Code principles
  • Familiarity with CI/CD platforms and automation pipelines
  • Experience with Kubernetes and container orchestration

Job no. JOB-R8PYA

Sii ensures that all hiring decisions are made solely on the basis of qualifications and competence. We are committed to equal and fair treatment of all, regardless of legally protected characteristics. At Sii, we promote a diverse and inclusive work environment, in full compliance with applicable anti-discrimination laws.

Benefits For You

  • Great Place to Work
  • Solid financial situation
  • Contracts with the biggest brands
  • Centre of internal trainings
  • Many experts you can learn from
  • Open and accessible management team
  • Profit sharing
  • Passion Sponsorship program
  • Regular integration events and trips
  • Comfortable and well-equipped offices
  • MySii app
  • Medical care

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

That is every opening in this category and country

FDE AI/ Solutions Architect (AI, Python/Data)Provectus

Apply on the employer's site