Senior Cloud Platform Engineer with AI Enablement Job at Algoteque (Warszawa)

Senior Solution Engineer - Cloud & AI Data Platform

Are you insatiably curious, deeply passionate about the realm of databases and a...

Location

United States , Multiple Locations

Salary:

106400.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Master's Degree in Computer Science, Information Technology, or related field AND 3+ years technical pre-sales or technical consulting experience OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience OR 5+ years technical pre-sales or technical consulting experience OR equivalent experience
This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.

Job Responsibility

Drive technical sales with decision makers using demos and PoCs to influence solution design and enable production deployments
Lead hands-on engagements—hackathons and architecture workshops—to accelerate adoption of Microsoft's cloud platforms
Build trusted relationships with platform leads, co-designing secure, scalable architectures and solutions
Resolve technical blockers and objections, collaborating with engineering to share insights and improve products
Maintain deep knowledge in Analytics Portfolio: Microsoft Fabric (OneLake, DW, real-time intelligence, BI, Copilot), Azure Databricks, Purview Data Governance and Azure Databases: SQL DB, Cosmos DB, PostgreSQL
Maintain and grow knowledge in on-prem EDW (Teradata, Netezza, Exadata), Hadoop & BI solutions
Represent Microsoft through thought leadership in cloud Database & Analytics communities and customer forums
Embody our culture and values

What we offer

Certain roles may be eligible for benefits and other compensation

Fulltime

Senior Software Engineer, AI Platform and Enablement

We're building a next-generation AI-powered platform and web application for cre...

Location

United States , San Francisco

Salary:

180000.00 - 286000.00 USD / Year

Descript

Expiration Date

Until further notice

Requirements

Experience in deploying and managing AI models in production
Experience with the tools of large volume data pipelines like spark, flume, dask, etc.
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and container technologies (Docker, Kubernetes)
Knowledge of DevOps and MLOps best practices
Strong problem-solving abilities and excellent communication skills

Job Responsibility

Build, maintain, and standardize third-party model integrations, including consulting for other engineering teams with AI model integration needs
Design, implement, and maintain our AI infrastructure supporting our machine learning life cycle, including data ingestion pipelines, training developer experience and infrastructure, evaluation frameworks, and deployments / GPU infrastructure
Collaborate with Product Managers, Research Engineers, and AI Researchers to understand their infrastructure needs and ensure our AI systems are robust, scalable, and efficient
Optimize and scale our models and algorithms for efficient inference
Deploy, monitor, and manage AI models in production

What we offer

Generous healthcare package
401k matching program
Catered lunches
Flexible vacation time

Fulltime

Senior Cloud Solution Architect - Cloud & AI Data Platform

We are looking for a Senior Cloud Solution Architect – Cloud & AI Data Platform ...

Location

United States , Multiple Locations

Salary:

106400.00 - 251900.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 4+ years experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting OR equivalent experience
This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.

Job Responsibility

Operates according to required operational excellence and proven practice standards throughout all sales stages/activities/tools of record (e.g., pipeline updates, time tracking)
Collaborates across Microsoft and customer/partner teams through on-strategy delivery to achieve customer/partner objectives and increase customer/partner satisfaction
Proactively manages business and technical risks, adapts methodology and applies governance principles to identify, communicate, and minimize business and technical risks
Executes work in compliance with industry and Microsoft guidelines and procedures
Continuously prioritizes among competing demands in their work and identifies where impact occurs with customers, ensuring alignment with business priorities and goals
Delivers solutions in line with company methodologies (e.g., product offerings such as value-based deliverables [VBDs], advice, training, technical validation), ensuring proven practices and patterns are followed to prepare customers for operational readiness and achievement of their business goals and targets
Leveraging knowledge of change management proven practices and/or involving the change management team, proactively helps the customer deploy for long-term organizational adoption to increase customer satisfaction and drive consumption/usage
Guides customers/partners towards a well-architected (e.g., secure, resilient, artificial intelligence [AI]-enabled), and cost- and performance-optimized solution to increase retention and expansion opportunities
Provides feedback to Unified Delivery Team on VBDs to refine and further develop content
Proactively identifies new opportunities for Consumption, Usage & Unified expansion (especially Enhanced Solutions) at scale based on business value to customer/partner and clear understanding of the Microsoft value proposition for supported platforms to empower cloud success, foster and strengthen security and resiliency, and drive AI innovation

What we offer

Certain roles may be eligible for benefits and other compensation.

Fulltime

New

Senior Cloud AI Engineer

At Teradata, we believe that people thrive when empowered with better informatio...

Location

India , Bengaluru; Hyderabad; Pune

Salary:

Not provided

Teradata

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science or equivalent from a recognized institution
4+ years of experience in infrastructure, networking, devops or cloud technologies
Hands-on expertise with public cloud providers such as AWS, Azure, or GCP, cloud APIs and SDKs, or infrastructure components such as VPC/VNet, API gateways, storage or compute
Experience with virtualization/container orchestration technologies like Kubernetes, Istio or Docker
Advanced proficiency in automation tools like Terraform and Helm
Experience with configuration management tools like Chef or Puppet
Strong proficiency in languages like Python, Go, or Bash for services development and scripting
Familiarity with CI/CD pipelines and tools such as Jenkins, GitHub Actions or ArgoCD
Good understanding of design principles, distributed system patterns
Familiarity with security, compliance, IAM and observability

Job Responsibility

Design, develop, and maintain high quality cloud native or on-prem infrastructure with an emphasis on scalability, availability, resiliency, and performance
Design and review large-scale distributed systems supporting multi cloud deployments
Use IaC and automation tools such as Terraform to ensure infrastructure changes are reliable, repeatable, and version controlled
Develop self-service platforms and tools that improve developer productivity and streamline deployment lifecycles
Collaborate with cross-functional engineers and product partners to shape the product and enable consistent delivery of end to end features
Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability
Work with SQL and/or NoSQL databases to implement efficient data models and service access patterns
Implement comprehensive monitoring, logging, and alerting systems
Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs)
Use AI powered engineering tools to improve development quality, speed, and productivity

What we offer

people-first culture
flexible working model
focus on wellbeing
Diversity, Equity, and Inclusion

Fulltime

Senior ML Engineer - AI Platform & Agents

We are building agentic AI into the core of our product and need someone who can...

Location

France , Bordeaux

Salary:

Not provided

PhantomBuster

Expiration Date

Until further notice

Requirements

5+ years of experience as an ML Engineer, AI Engineer, or Software Engineer with a strong AI focus
Hands-on experience building AI agents using frameworks such as LangChain, Amazon Bedrock AgentCore, or similar
Strong understanding of LLM-based systems: prompt engineering, agent orchestration, tool use, and multi-agent workflows
Familiarity with MCP (Model Context Protocol) and experience integrating agents with external APIs or data sources
Experience working with Agents for Amazon Bedrock AgentCore or similar agent setups
Strong understanding of machine learning algorithms, statistical methods, and data preprocessing techniques
Experience with cloud platforms for model training and deployment, especially AWS
Proficiency in Python, including LangChain, and standard data libraries (Pandas, NumPy, etc.)
Fluency in English

Job Responsibility

Define and evolve our infrastructure to allow for better ML and AI capabilities, with a focus on LLM-based and agentic systems
Contribute to the development and expansion of our agentic AI framework powered by AWS Bedrock, enabling both internal tools and customer-facing features
Identify, source, and refine datasets to allow tuning models, powering retrieval pipelines, or expanding agentic workflows
Pre-process data by using techniques such as data cleaning, feature engineering, and transformation
Train, evaluate, and deploy both LLM-based systems and traditional machine learning models into production
Monitor, debug, and continuously improve deployed models and AI tools
Support machine learning usage throughout the company, including selecting the right modeling approach for the use case (LLM vs. traditional ML)
Support the integration and use of LLMs, including approaches such as fine-tuning, prompt tuning, and retrieval-augmented generation (RAG), to improve accuracy

What we offer

International team
Fun team building events
€40/month for remote work
Flexible working time
Home office budget up to €1500
100% of an Alan Blue subscription
Lunch vouchers - €8 (50% The Phantom Company) / worked day
Partnership with MokaCare
€70 a month benefit for entertainment expenses
Book Allowance and Sharing Program

Senior ML Engineer - AI Platform & Agents

Join PhantomBuster as a Senior ML Engineer to build agentic AI with AWS Bedrock,...

Location

France; Spain; Portugal

Salary:

Not provided

PhantomBuster

Expiration Date

Until further notice

Requirements

5+ years of experience as an ML Engineer, AI Engineer, or Software Engineer with a strong AI focus
Hands-on experience building AI agents using frameworks such as LangChain, Amazon Bedrock AgentCore, or similar
Strong understanding of LLM-based systems: prompt engineering, agent orchestration, tool use, and multi-agent workflows
Familiarity with MCP (Model Context Protocol) and experience integrating agents with external APIs or data sources
Experience working with Agents for Amazon Bedrock AgentCore or similar agent setups
Strong understanding of machine learning algorithms, statistical methods, and data preprocessing techniques
Experience with cloud platforms for model training and deployment, especially AWS
Proficiency in Python, including LangChain, and standard data libraries (Pandas, NumPy, etc.)
Fluency in English

Job Responsibility

Define and evolve our infrastructure to allow for better ML and AI capabilities, with a focus on LLM-based and agentic systems
Contribute to the development and expansion of our agentic AI framework powered by AWS Bedrock, enabling both internal tools and customer-facing features
Identify, source, and refine datasets to allow tuning models, powering retrieval pipelines, or expanding agentic workflows
Pre-process data by using techniques such as data cleaning, feature engineering, and transformation
Train, evaluate, and deploy both LLM-based systems and traditional machine learning models into production
Monitor, debug, and continuously improve deployed models and AI tools
Support machine learning usage throughout the company, including selecting the right modeling approach for the use case (LLM vs. traditional ML)
Support the integration and use of LLMs, including approaches such as fine-tuning, prompt tuning, and retrieval-augmented generation (RAG), to improve accuracy

What we offer

Fully remote working environment (France, Spain, or Portugal)
Real ownership: you will define how agentic AI is built at PhantomBuster, not follow someone else's decisions
Freedom to research and adopt new technologies as the space evolves & to make an impact at a small, self-funded, and profitable tech startup by laying the foundation for machine learning and AI
Collaborative and open-minded culture based on rationality, humility, honesty, and long-term thinking
International team
Fun team building events
€40/month for remote work
Flexible working time
Home office budget up to €1500
100% of an Alan Blue subscription (french-based contracts)

Fulltime

Senior Solution Engineer - Cloud & AI Apps

Are you insatiably curious, deeply passionate about AI and modern application de...

Location

Singapore , Singapore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

8+ years of experience in technical pre-sales, solution architecture, or technical consulting, OR equivalent experience
Strong hands-on experience designing and delivering cloud-native applications on Azure or equivalent platforms
Solid understanding of AI application architectures, including model integration, orchestration, and deployment
Proven ability to engage with senior technical and business stakeholders and influence architecture decisions
Experience leading architecture design sessions, POCs, demos, or technical workshops
Strong communication skills with the ability to explain complex technical concepts clearly and confidently

Job Responsibility

Lead and own end-to-end technical engagements with customers, from discovery through architecture design, POCs, and production readiness
Partner with account teams to drive and win the customer technical decision by aligning Microsoft Cloud & AI capabilities to customer business outcomes
Act as a trusted technical advisor to CIOs, CDOs, CTOs, architects, and senior developers across industries
Translate complex customer requirements into secure, scalable, and compliant AI application architectures
Design and present architectures for AI-powered applications and agents, including cloud-native, hybrid, and multi-tier solutions
Lead architecture design sessions, demos, hackathons, and proofs of concept showcasing Microsoft AI and application platforms
Adapt and extend reference architectures to meet industry, regulatory, and enterprise-scale requirements
Position Microsoft solutions competitively by articulating technical differentiation and value
Apply deep expertise across Azure AI, application services, and agent-based architectures to solve customer challenges
Guide customers on building, deploying, and managing AI apps and intelligent agents at scale

Fulltime

Senior Machine Learning Engineer, AI Platform

The AI Platform team is responsible for building the foundational infrastructure...

Location

United States; Canada

Salary:

139000.00 - 218000.00 USD / Year

Mozilla

Expiration Date

Until further notice

Requirements

Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
Hands-on experience working with GPU-based workloads and accelerated computing in production settings
Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
Ability to independently scope and drive technical initiatives while balancing product and operational priorities
Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams

Job Responsibility

Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews

What we offer

Generous performance-based bonus plans
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

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Senior Cloud Platform Engineer with AI Enablement

Job Description

Job Responsibility

Requirements

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