We are launching a strategic pool of AI specialists to accelerate the growth of our AI Practice and turn strong market demand into scalable, repeatable capabilities. This role goes beyond project delivery-it is about shaping how AI is built, shared, and scaled across the company.

As part of this group, you will play a key role in internal capability development, with a strong focus on designing and evolving AI Accelerators-reusable frameworks, templates, and reference architectures covering GenAI, LLM-based solutions, ML pipelines, and cloud-native AI systems. These accelerators will become the backbone of our AI offerings, enabling faster delivery, higher quality, and consistent technical standards across projects.

A second core dimension of the role is knowledge leadership. Strategic hires will actively contribute to internal knowledge-sharing initiatives: technical deep dives, hands-on workshops, demos, and best-practice sessions covering topics such as GenAI orchestration, RAG, model deployment, prompt and system design, observability, and cost-efficient AI architectures. You will help raise the overall AI maturity of the organization while mentoring engineers and influencing technical direction. In addition, members of this group will act as AI project jumpstarters, joining new client engagements for up to 50% allocation over 1-2 months. In this capacity, you will help define solution architectures, validate technical approaches, build initial prototypes, and set strong engineering foundations before teams scale. This gives you exposure to diverse domains and cutting-edge AI use cases while maximizing your impact across multiple initiatives.

Project Description

We are looking for a highly skilled and innovative Machine Learning Engineer to develop and expand our Generative AI and Computer Vision capabilities. This role involves accelerating Technical Sales Support, Architecture and PoC development.

Technologies

• Python
• Git, CI/CD practices for ML and data pipelines
• AWS and/or Azure
• PyTorch, TensorFlow
• MLflow
• LLMs and NLP tasks
• Generative AI concepts
• LangChain/LangGraph, LlamaIndex
• Qdrant, Pinecone, Weaviate, FAISS or similar
• RNNs, Transformers
• Dataset labeling, annotation tools (e.g., Label Studio, CVAT)
• Prometheus, Grafana, DataDog, OpenTelemetry
• YOLO, SDD
• Segmentation models
• Image Classification

What You'll Do

• Lead the design, development, and deployment of scalable ML services;
• Architect and implement AI/ML solutions, ensuring model quality, governance, and security;
• Optimize ML workflows for performance and cost efficiency on cloud platforms (AWS, Azure, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand ML requirements;
• Mentor and guide junior engineers, promoting best practices in ML engineering;
• Develop and maintain documentation, ML models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production for ML pipelines and environments;
• Stay up-to-date with emerging trends and technologies in AI/ML field;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in ML engineering, with at least 1 years of hands-on experience with LLMs;
• Strong proficiency in Python;
• Experience with cloud data platforms (AWS and/or Azure);
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for ML engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Company Background

Our client is a leading global data center provider delivering hyperscale and edge infrastructure solutions across the Americas, EMEA, and Asia-Pacific. With 80+ data centers in 20+ countries, they partner with industry leaders such as Google, Oracle, NVIDIA, and Microsoft Azure to power the world’s digital infrastructure. Recognized as a USA TODAY Top Workplace for four consecutive years, the company continues to expand its global footprint and customer ecosystem.

Project Description

We are looking for a Cloud Infrastructure Engineer to help shape and deliver a modern cloud and hybrid IT strategy across Azure, AWS, and GCP. In this role, you will design scalable, secure, and cost-effective infrastructure that supports enterprise applications, hybrid connectivity, and next-generation data and AI/ML workloads.

Technologies

• Azure ecosystem
• Azure DevOps
• GCP / AWS
• Infrastructure as Code: Bicep
• Windows Server
• Microsoft SQL Server

What You'll Do

• Lead the assessment and modernization of enterprise cloud workloads, defining migration roadmaps across retain, re-platform, refactor, and retire scenarios;
• Design governed multi-cloud landing zones across Azure, AWS, and/or GCP, standardizing networking, identity, policy, and account/subscription topology through Terraform and Bicep;
• Establish cloud-agnostic infrastructure practices, reusable IaC modules, and automated provisioning standards to reduce manual operations and subscription sprawl;
• Govern identity and access across cloud platforms, SaaS applications, and CI/CD workloads using Microsoft Entra ID, conditional access, workload identity federation, and service principal controls;
• Architect secure hybrid and cross-cloud connectivity, including ExpressRoute, SD-WAN, traffic segmentation, and low-latency data transfer patterns;
• Implement zero-trust security controls for IT/OT boundaries, including inspected and policy-enforced traffic flows for SCADA, HMI, ICS, and enterprise systems;
• Design resilient, highly available cloud architectures with defined RTO/RPO targets and automated disaster recovery validation;
• Build platform services, CI/CD templates, and self-service infrastructure capabilities that enable internal teams to consume cloud services through documented standards and APIs;
• Implement governance, policy-as-code, and FinOps practices to enforce security, compliance, cost tagging, spend attribution, and cloud cost optimization;
• Support strategic modernization initiatives, including Kubernetes adoption, application containerization, database optimization, and reduction of Windows server licensing costs;

Job Requirements

• 7+ years of experience in cloud infrastructure engineering, with deep hands-on expertise in Microsoft Azure and production experience with at least two major cloud providers, such as Azure, AWS, or GCP;
• Strong experience with cloud networking, IAM, compute, IaaS/PaaS services, and Microsoft Entra ID / Azure AD, including conditional access, workload identity federation, SAML/SCIM, and service principal governance;
• Proven expertise in IaC using Terraform and/or Bicep, including governed landing zones, module registries, and cloud infrastructure migration;
• Hands-on experience designing and operating CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools, including pipeline-as-code, security scanning, and deployment gates;
• Solid understanding of zero-trust architecture, IT/OT boundary security, and industrial control environments such as SCADA, HMI, and ICS;
• Experience designing and validating disaster recovery architectures across regions and cloud providers, including RTO/RPO definition and automated failover testing;
• Familiarity with FinOps practices and tools, including cost tagging, spend attribution, showback/chargeback models, CloudHealth, CloudCor, or native cloud cost tools;
• Experience with policy-as-code frameworks such as Azure Policy, AWS SCPs, GCP Organization Policies, or Open Policy Agent;
• English level: B2 or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Project Description

We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.

Technologies

• Databricks (including Spark, Delta Lake, MLflow)
• Python/Scala
• SQL
• ETL concepts
• Distributed data processing
• Data warehousing
• Cloud Platforms & Storage

What You'll Do

• Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
• Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
• Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
• Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
• Develop and maintain documentation, data models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
• Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
• Strong proficiency in Python and/or Scala for data processing;
• Deep understanding of distributed data processing, data warehousing, and ETL concepts;
• Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
• Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Sep 25, 2025 12:50

Why this role exists:

This role exists to bridge the gap between ambitious business goals and high-performance engineering reality. You’ll help us scale our technical ecosystem by taking full ownership of architectural blueprints, governance standards, and the long-term stability of our distributed systems.

What you’ll drive:

Strategy & Architecture Design

• Define and evangelize technology principles that balance short-term delivery with long-term system vitality.
• Architect distributed systems using Domain-Driven Design (DDD), CQRS, and Event-Driven Architecture (EDA).
• Select and validate the right tools—from Kafka streams to NoSQL stores—to solve specific scale bottlenecks.

Resilience & Governance

• Design for failure by implementing patterns like Circuit Breaker, Bulkhead, and advanced Rate-limiting.
• Establish governance frameworks that unblock developers rather than slowing them down with bureaucracy.
• Optimize data strategies, including sharding, replication, and performance tuning for SQL/NoSQL databases under heavy load.

Delivery & Cloud Evolution

• Build scalable infrastructure using Kubernetes, Docker, and Infrastructure as Code (Terraform/Ansible).
• Modernize CI/CD pipelines to ensure automated, secure, and rapid deployments.
• Drive FinOps initiatives to ensure our cloud architecture is as cost-efficient as it is performant.

Technical Leadership

• Unblock engineering teams by breaking down complex problems into clear, documented architectural blueprints.
• Lead architecture reviews and mentor senior engineers to foster a culture of technical excellence.

What makes you a GR8 fit:

Must-have

• 5+ years in senior/lead engineering roles with a proven track record in Microservices, EDA, and DDD.
• Deep understanding of CAP theorem, ACID properties, and implementing fault-tolerance patterns.
• Hands-on mastery of AWS or Azure, including Kubernetes, Docker, and Terraform (IaC).
• Expert-level SQL/NoSQL knowledge, including database sharding, replication, and query optimization.
• Proficiency in Kafka (architecture, stream processing, and optimization for reliability).
• Master’s degree in Computer Science or a related technical field.

Nice-to-have

• Understanding of IAM, PKI, and building secure VPC/Hybrid cloud environments.
• Experience with GitLab CI/GitHub Actions and optimizing cloud infrastructure costs.
• Designing monitoring strategies using APM tools and logging frameworks for full system visibility.
• Proven ability to migrate monoliths to cloud-native architectures without downtime.
• Experience in technical mentoring, code reviews, and driving engineering excellence across teams.

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