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.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

4-month engagement with the possibility of extension

Project Tech Stack

Databricks, Microsoft Azure, Medallion Architecture, Star Schema / Dimensional Modelling, Fact & Dimension tables, Databricks SQL, T-SQL, Python, Azure DevOps CI/CD, Git-based deployment pipelines

What You’ll Do  

• Rapidly review and understand the original Statement of Work, change requests, and any pre-existing contractual dependencies
• Audit the current state of the Databricks environment: what has been built, its quality, and its alignment to the agreed design
• Identify root causes for delivery gaps — distinguishing between client-side blockers, scope ambiguity, and engineering shortfalls
• Assess the medallion architecture (Bronze / Silver / Gold) and the ADF pipeline design against best practice and the client's requirements
• Review all outstanding work items (including dependent database views, gold views, ingestion, test framework, and UAT artefacts) and produce a clear, honest picture of the remaining effort
• Validate and, where necessary, correct or redesign the existing solution architecture to ensure it is fit for purpose, scalable, and maintainable
• Own the technical design for all remaining deliverables: ADF pipelines, Databricks SQL views, medallion layers, Unity Catalog, and CI/CD deployment via Azure DevOps
• Ensure architectural decisions are documented clearly and are explainable to both technical and non-technical client stakeholders
• Define the reconciliation and testing framework for view validation against SQL Server source systems
• Lead and execute the engineering delivery of all remaining scope, including: porting SQL Server views to Databricks SQL, building and validating ADF pipelines (batch ingestion), implementing gold-layer dimensional models and analytic views, deploying via Azure DevOps CI/CD pipelines (Test and Production environments)
• Produce high-quality, well-documented, maintainable code — not quick fixes
• Execute or oversee the reconciliation framework to prove view correctness against source systems
• Manage dependencies on the client (CDC enablement, SQL account provisioning, UAT availability) and escalate blockers promptly to the Engagement Lead
• Produce a realistic, structured delivery plan covering all remaining scope, with clear milestones, dependencies, and acceptance criteria
• Support the Engagement Lead in presenting the recovery plan to the client for sign-off
• Attend client-facing working sessions as the technical authority — you must be credible and confident communicating with both IT and commercial stakeholders
• Support the delivery management function with regular, accurate progress reporting

What You Bring 

• Expert-level proficiency in Azure Data Factory: pipeline design, linked services, integration runtimes (including Self-Hosted IR), incremental load patterns, and CDC
• Strong command of Azure Data Lake Storage Gen2, Unity Catalog, and Azure networking fundamentals relevant to data platform connectivity (VNets, Private Endpoints)
• Hands-on experience with Azure DevOps for CI/CD pipeline construction covering Databricks and ADF deployment across Dev / Test / Prod environments
• Familiarity with Microsoft Purview for data governance and lineage (desirable)
• Deep, hands-on Databricks experience — this is not a theoretical understanding; you must have delivered real solutions on the platform
• Expertise in Databricks SQL, Delta Lake, and the medallion architecture (Bronze / Silver / Gold)
• Ability to design and implement performant Databricks SQL views at scale, including complex join patterns, cross-database references, and performance validation
• Experience with Unity Catalog configuration and RBAC
• Familiarity with Databricks Lakeflow (desirable)
• Strong T-SQL / SQL Server background — you will be porting SQL Server views and need to understand source system data structures across OLTP and analytical databases
• Proven ability to design and implement fact/dimension tables, staging tables, and analytic models in a lakehouse context
• Experience building and running reconciliation frameworks to validate migrated data against source systems
• Solid Python skills for pipeline logic, test scripting, and utility development
• Demonstrated experience designing greenfield modern data platforms — you must be able to evidence solutions you have architected from scratch
• Demonstrated experience leading modernisation or transformation of brownfield data environments — migrating legacy reporting layers, rationalising fragmented data estates, or re-platforming to cloud-native architectures
• Ability to produce clear, concise architecture artefacts: solution design documents, data flow diagrams, entity models, and deployment architecture
• Sound understanding of data modelling — conceptual, logical, and physical — in the context of Lakehouse and dimensional design
• Proven ability to operate in a consulting or client-facing environment: credible, articulate, and capable of managing expectations under pressure
• Experience producing and owning delivery plans — not just contributing to them
• Comfortable working in a recovery or turnaround context, where rapid assessment and honest communication are more important than defending prior decisions
• Experience working under an engagement lead / principal and operating with a high degree of autonomy within that structure

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

6-month engagement with the possibility of extension

What You’ll Do  

• Lead structured technical discovery with the hardware and platform engineering teams to establish the API surface, platform readiness, and target workload definitions
• Author the Architecture Decision Record (ADR) documenting the integration approach, technology choices, and key design decisions
• Define the requirements baseline, functional and non-functional, and produce the risk register
• Negotiate and agree the revised Statement of Work for Phases 1 and 2 with the client
• Establish the reference workload definition and benchmark criteria to be used through the POC
• Maintain technical governance and architectural coherence across the integration build
• Direct the engineering team on component delivery: workload adapter, hardware dispatch client, telemetry bridge, and any required platform-side changes
• Manage the client relationship on a day-to-day basis: progress reporting, risk escalation, and gate reviews
• Review and sign off integration components before gate conditions are assessed
• Lead knowledge transfer and runbook acceptance sessions with client engineering teams
• Support the customer Proof of Value demonstration in an advisory capacity

What You Bring 

• Demonstrable background in cloud platform architecture, distributed systems, and API design — REST and gRPC in particular
• Experience integrating third-party hardware or specialised compute into cloud scheduling and resource management layers
• Familiarity with workload orchestration: Kubernetes, custom schedulers, resource plugins, or equivalent
• Working knowledge of observability tooling: OpenTelemetry, Prometheus, Grafana, or comparable stacks
• Comfort operating across the full stack, from infrastructure (IaC, networking, cloud providers) to API and platform layers
• SRE background or equivalent: SLO definition, telemetry design, incident response, and operational documentation
• Ability to design for observability and failure modes from the outset, not as a post-build afterthought
• Experience producing runbooks and operational documentation for technical handover
• Proven ability to lead client-facing technical engagements, managing expectations, communicating risk, and maintaining trust in ambiguous early-stage programmes
• Comfortable working with non-traditional technical counterparts, such as hardware scientists who may not be experienced platform API producers
• Skilled at structured requirements elicitation under significant uncertainty — able to extract requirements through interviews, prototypes, and reference examples rather than documentation
• Experience producing Architecture Decision Records, revised SOW documents, and risk registers as formal engagement outputs
• Experience operating as a senior contractor or fractional leader, comfortable with part-time engagement structures and accountability for commercial gate conditions without full-time oversight
• Able to take ownership of engagement quality and client confidence independently

Nice to Have

• Prior exposure to custom silicon, FPGA integration, or specialised AI accelerator hardware
• Experience in sovereign cloud, data sovereignty, or regulated compute environments
• Familiarity with AI/ML workload types: inference serving, training pipelines, batch processing
• Experience with M2M identity, workload authentication, and platform governance patterns
• Background in early-stage or venture-backed technology companies where engineering rigour and commercial pragmatism must coexist

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

6-month engagement with the possibility of extension

What You’ll Do  

• Lead structured technical discovery with the hardware and platform engineering teams to establish the API surface, platform readiness, and target workload definitions
• Author the Architecture Decision Record (ADR) documenting the integration approach, technology choices, and key design decisions
• Define the requirements baseline, functional and non-functional, and produce the risk register
• Negotiate and agree the revised Statement of Work for Phases 1 and 2 with the client
• Establish the reference workload definition and benchmark criteria to be used through the POC
• Maintain technical governance and architectural coherence across the integration build
• Direct the engineering team on component delivery: workload adapter, hardware dispatch client, telemetry bridge, and any required platform-side changes
• Manage the client relationship on a day-to-day basis: progress reporting, risk escalation, and gate reviews
• Review and sign off integration components before gate conditions are assessed
• Lead knowledge transfer and runbook acceptance sessions with client engineering teams
• Support the customer Proof of Value demonstration in an advisory capacity

What You Bring 

• Demonstrable background in cloud platform architecture, distributed systems, and API design — REST and gRPC in particular
• Experience integrating third-party hardware or specialised compute into cloud scheduling and resource management layers
• Familiarity with workload orchestration: Kubernetes, custom schedulers, resource plugins, or equivalent
• Working knowledge of observability tooling: OpenTelemetry, Prometheus, Grafana, or comparable stacks
• Comfort operating across the full stack, from infrastructure (IaC, networking, cloud providers) to API and platform layers
• SRE background or equivalent: SLO definition, telemetry design, incident response, and operational documentation
• Ability to design for observability and failure modes from the outset, not as a post-build afterthought
• Experience producing runbooks and operational documentation for technical handover
• Proven ability to lead client-facing technical engagements, managing expectations, communicating risk, and maintaining trust in ambiguous early-stage programmes
• Comfortable working with non-traditional technical counterparts, such as hardware scientists who may not be experienced platform API producers
• Skilled at structured requirements elicitation under significant uncertainty — able to extract requirements through interviews, prototypes, and reference examples rather than documentation
• Experience producing Architecture Decision Records, revised SOW documents, and risk registers as formal engagement outputs
• Experience operating as a senior contractor or fractional leader, comfortable with part-time engagement structures and accountability for commercial gate conditions without full-time oversight
• Able to take ownership of engagement quality and client confidence independently

Nice to Have

• Prior exposure to custom silicon, FPGA integration, or specialised AI accelerator hardware
• Experience in sovereign cloud, data sovereignty, or regulated compute environments
• Familiarity with AI/ML workload types: inference serving, training pipelines, batch processing
• Experience with M2M identity, workload authentication, and platform governance patterns
• Background in early-stage or venture-backed technology companies where engineering rigour and commercial pragmatism must coexist

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

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 Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

4-month engagement with the possibility of extension

Project Tech Stack

Databricks, Microsoft Azure, Medallion Architecture, Star Schema / Dimensional Modelling, Fact & Dimension tables, Databricks SQL, T-SQL, Python, Azure DevOps CI/CD, Git-based deployment pipelines

What You’ll Do  

• Rapidly review and understand the original Statement of Work, change requests, and any pre-existing contractual dependencies
• Audit the current state of the Databricks environment: what has been built, its quality, and its alignment to the agreed design
• Identify root causes for delivery gaps — distinguishing between client-side blockers, scope ambiguity, and engineering shortfalls
• Assess the medallion architecture (Bronze / Silver / Gold) and the ADF pipeline design against best practice and the client's requirements
• Review all outstanding work items (including dependent database views, gold views, ingestion, test framework, and UAT artefacts) and produce a clear, honest picture of the remaining effort
• Validate and, where necessary, correct or redesign the existing solution architecture to ensure it is fit for purpose, scalable, and maintainable
• Own the technical design for all remaining deliverables: ADF pipelines, Databricks SQL views, medallion layers, Unity Catalog, and CI/CD deployment via Azure DevOps
• Ensure architectural decisions are documented clearly and are explainable to both technical and non-technical client stakeholders
• Define the reconciliation and testing framework for view validation against SQL Server source systems
• Lead and execute the engineering delivery of all remaining scope, including: porting SQL Server views to Databricks SQL, building and validating ADF pipelines (batch ingestion), implementing gold-layer dimensional models and analytic views, deploying via Azure DevOps CI/CD pipelines (Test and Production environments)
• Produce high-quality, well-documented, maintainable code — not quick fixes
• Execute or oversee the reconciliation framework to prove view correctness against source systems
• Manage dependencies on the client (CDC enablement, SQL account provisioning, UAT availability) and escalate blockers promptly to the Engagement Lead
• Produce a realistic, structured delivery plan covering all remaining scope, with clear milestones, dependencies, and acceptance criteria
• Support the Engagement Lead in presenting the recovery plan to the client for sign-off
• Attend client-facing working sessions as the technical authority — you must be credible and confident communicating with both IT and commercial stakeholders
• Support the delivery management function with regular, accurate progress reporting

What You Bring 

• Expert-level proficiency in Azure Data Factory: pipeline design, linked services, integration runtimes (including Self-Hosted IR), incremental load patterns, and CDC
• Strong command of Azure Data Lake Storage Gen2, Unity Catalog, and Azure networking fundamentals relevant to data platform connectivity (VNets, Private Endpoints)
• Hands-on experience with Azure DevOps for CI/CD pipeline construction covering Databricks and ADF deployment across Dev / Test / Prod environments
• Familiarity with Microsoft Purview for data governance and lineage (desirable)
• Deep, hands-on Databricks experience — this is not a theoretical understanding; you must have delivered real solutions on the platform
• Expertise in Databricks SQL, Delta Lake, and the medallion architecture (Bronze / Silver / Gold)
• Ability to design and implement performant Databricks SQL views at scale, including complex join patterns, cross-database references, and performance validation
• Experience with Unity Catalog configuration and RBAC
• Familiarity with Databricks Lakeflow (desirable)
• Strong T-SQL / SQL Server background — you will be porting SQL Server views and need to understand source system data structures across OLTP and analytical databases
• Proven ability to design and implement fact/dimension tables, staging tables, and analytic models in a lakehouse context
• Experience building and running reconciliation frameworks to validate migrated data against source systems
• Solid Python skills for pipeline logic, test scripting, and utility development
• Demonstrated experience designing greenfield modern data platforms — you must be able to evidence solutions you have architected from scratch
• Demonstrated experience leading modernisation or transformation of brownfield data environments — migrating legacy reporting layers, rationalising fragmented data estates, or re-platforming to cloud-native architectures
• Ability to produce clear, concise architecture artefacts: solution design documents, data flow diagrams, entity models, and deployment architecture
• Sound understanding of data modelling — conceptual, logical, and physical — in the context of Lakehouse and dimensional design
• Proven ability to operate in a consulting or client-facing environment: credible, articulate, and capable of managing expectations under pressure
• Experience producing and owning delivery plans — not just contributing to them
• Comfortable working in a recovery or turnaround context, where rapid assessment and honest communication are more important than defending prior decisions
• Experience working under an engagement lead / principal and operating with a high degree of autonomy within that structure

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

4-month engagement with the possibility of extension

Project Tech Stack

Databricks, Microsoft Azure, Medallion Architecture, Star Schema / Dimensional Modelling, Fact & Dimension tables, Databricks SQL, T-SQL, Python, Azure DevOps CI/CD, Git-based deployment pipelines

What You’ll Do  

• Rapidly review and understand the original Statement of Work, change requests, and any pre-existing contractual dependencies
• Audit the current state of the Databricks environment: what has been built, its quality, and its alignment to the agreed design
• Identify root causes for delivery gaps — distinguishing between client-side blockers, scope ambiguity, and engineering shortfalls
• Assess the medallion architecture (Bronze / Silver / Gold) and the ADF pipeline design against best practice and the client's requirements
• Review all outstanding work items (including dependent database views, gold views, ingestion, test framework, and UAT artefacts) and produce a clear, honest picture of the remaining effort
• Validate and, where necessary, correct or redesign the existing solution architecture to ensure it is fit for purpose, scalable, and maintainable
• Own the technical design for all remaining deliverables: ADF pipelines, Databricks SQL views, medallion layers, Unity Catalog, and CI/CD deployment via Azure DevOps
• Ensure architectural decisions are documented clearly and are explainable to both technical and non-technical client stakeholders
• Define the reconciliation and testing framework for view validation against SQL Server source systems
• Lead and execute the engineering delivery of all remaining scope, including: porting SQL Server views to Databricks SQL, building and validating ADF pipelines (batch ingestion), implementing gold-layer dimensional models and analytic views, deploying via Azure DevOps CI/CD pipelines (Test and Production environments)
• Produce high-quality, well-documented, maintainable code — not quick fixes
• Execute or oversee the reconciliation framework to prove view correctness against source systems
• Manage dependencies on the client (CDC enablement, SQL account provisioning, UAT availability) and escalate blockers promptly to the Engagement Lead
• Produce a realistic, structured delivery plan covering all remaining scope, with clear milestones, dependencies, and acceptance criteria
• Support the Engagement Lead in presenting the recovery plan to the client for sign-off
• Attend client-facing working sessions as the technical authority — you must be credible and confident communicating with both IT and commercial stakeholders
• Support the delivery management function with regular, accurate progress reporting

What You Bring 

• Expert-level proficiency in Azure Data Factory: pipeline design, linked services, integration runtimes (including Self-Hosted IR), incremental load patterns, and CDC
• Strong command of Azure Data Lake Storage Gen2, Unity Catalog, and Azure networking fundamentals relevant to data platform connectivity (VNets, Private Endpoints)
• Hands-on experience with Azure DevOps for CI/CD pipeline construction covering Databricks and ADF deployment across Dev / Test / Prod environments
• Familiarity with Microsoft Purview for data governance and lineage (desirable)
• Deep, hands-on Databricks experience — this is not a theoretical understanding; you must have delivered real solutions on the platform
• Expertise in Databricks SQL, Delta Lake, and the medallion architecture (Bronze / Silver / Gold)
• Ability to design and implement performant Databricks SQL views at scale, including complex join patterns, cross-database references, and performance validation
• Experience with Unity Catalog configuration and RBAC
• Familiarity with Databricks Lakeflow (desirable)
• Strong T-SQL / SQL Server background — you will be porting SQL Server views and need to understand source system data structures across OLTP and analytical databases
• Proven ability to design and implement fact/dimension tables, staging tables, and analytic models in a lakehouse context
• Experience building and running reconciliation frameworks to validate migrated data against source systems
• Solid Python skills for pipeline logic, test scripting, and utility development
• Demonstrated experience designing greenfield modern data platforms — you must be able to evidence solutions you have architected from scratch
• Demonstrated experience leading modernisation or transformation of brownfield data environments — migrating legacy reporting layers, rationalising fragmented data estates, or re-platforming to cloud-native architectures
• Ability to produce clear, concise architecture artefacts: solution design documents, data flow diagrams, entity models, and deployment architecture
• Sound understanding of data modelling — conceptual, logical, and physical — in the context of Lakehouse and dimensional design
• Proven ability to operate in a consulting or client-facing environment: credible, articulate, and capable of managing expectations under pressure
• Experience producing and owning delivery plans — not just contributing to them
• Comfortable working in a recovery or turnaround context, where rapid assessment and honest communication are more important than defending prior decisions
• Experience working under an engagement lead / principal and operating with a high degree of autonomy within that structure

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

Project Duration  

6-month engagement with the possibility of extension

What You’ll Do  

• Lead structured technical discovery with the hardware and platform engineering teams to establish the API surface, platform readiness, and target workload definitions
• Author the Architecture Decision Record (ADR) documenting the integration approach, technology choices, and key design decisions
• Define the requirements baseline, functional and non-functional, and produce the risk register
• Negotiate and agree the revised Statement of Work for Phases 1 and 2 with the client
• Establish the reference workload definition and benchmark criteria to be used through the POC
• Maintain technical governance and architectural coherence across the integration build
• Direct the engineering team on component delivery: workload adapter, hardware dispatch client, telemetry bridge, and any required platform-side changes
• Manage the client relationship on a day-to-day basis: progress reporting, risk escalation, and gate reviews
• Review and sign off integration components before gate conditions are assessed
• Lead knowledge transfer and runbook acceptance sessions with client engineering teams
• Support the customer Proof of Value demonstration in an advisory capacity

What You Bring 

• Demonstrable background in cloud platform architecture, distributed systems, and API design — REST and gRPC in particular
• Experience integrating third-party hardware or specialised compute into cloud scheduling and resource management layers
• Familiarity with workload orchestration: Kubernetes, custom schedulers, resource plugins, or equivalent
• Working knowledge of observability tooling: OpenTelemetry, Prometheus, Grafana, or comparable stacks
• Comfort operating across the full stack, from infrastructure (IaC, networking, cloud providers) to API and platform layers
• SRE background or equivalent: SLO definition, telemetry design, incident response, and operational documentation
• Ability to design for observability and failure modes from the outset, not as a post-build afterthought
• Experience producing runbooks and operational documentation for technical handover
• Proven ability to lead client-facing technical engagements, managing expectations, communicating risk, and maintaining trust in ambiguous early-stage programmes
• Comfortable working with non-traditional technical counterparts, such as hardware scientists who may not be experienced platform API producers
• Skilled at structured requirements elicitation under significant uncertainty — able to extract requirements through interviews, prototypes, and reference examples rather than documentation
• Experience producing Architecture Decision Records, revised SOW documents, and risk registers as formal engagement outputs
• Experience operating as a senior contractor or fractional leader, comfortable with part-time engagement structures and accountability for commercial gate conditions without full-time oversight
• Able to take ownership of engagement quality and client confidence independently

Nice to Have

• Prior exposure to custom silicon, FPGA integration, or specialised AI accelerator hardware
• Experience in sovereign cloud, data sovereignty, or regulated compute environments
• Familiarity with AI/ML workload types: inference serving, training pipelines, batch processing
• Experience with M2M identity, workload authentication, and platform governance patterns
• Background in early-stage or venture-backed technology companies where engineering rigour and commercial pragmatism must coexist

English level

Upper-Intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Kimchi?

Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters - now we're building the execution layer where agents do real work.

Our Infrastructure today: multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API, and deployment flexibility from our GPUs to your VPC. The inference layer is the foundation. What we're hiring for sits on top of it: coding agents, agent runtimes, orchestration systems, and the reliability engineering that makes them actually finish things.

Tech Stack: TypeScript, Go, Kubernetes, AWS/GCP/Azure, MCP, Prometheus/Grafana/Loki, GitLab CI, ArgoCD.

Why harness engineering matters here
OpenAI and Anthropic ship models. They also ship one harness each - the scaffolding that turns a raw model into something that can plan, execute, recover, and complete work. We ship a different kind of harness: one built for cost-conscious, long-horizon autonomy, running on inference infrastructure we control end-to-end.
A decent model with a great harness beats a great model with a bad harness. We've watched this play out. The gap between what today's models can do and what you see them doing is largely a harness gap - and that gap is where we operate.

What you'll build
The ratchet.
Every time our agent makes a mistake, we engineer a solution so it never makes that mistake again. That means hooks that enforce constraints the model "knows" but forgets: pre-commit lint checks, permission gates, context compaction before the window fills. Success is silent, failures are verbose.

Long-horizon execution.
Our harness is built around spec-driven autonomy: meta-prompting, fresh context per task, worktree-per-slice git strategy, automatic replanning, crash recovery, stuck detection. We're implementing Ralph loops - when the model tries to exit, we intercept and reinject the goal into a fresh context. The agent reads state from disk and continues. Multi-session, multi-day work, without context rot.

Planner/executor splits.
Planning with a reasoning model, executing with a fast one, evaluating with a third. Separating generation from evaluation beats self-verification because agents reliably skew positive when grading their own work.

The harness surface.
CLI, TUI, MCP integration, sandboxed execution, telemetry. Our AGENTS.md is short - every line traces to a specific thing that went wrong. TypeScript on the surface, Go where it matters.

Memory and context.
Moving agents off laptops, giving them state that survives across sessions, managing context so information lands where it's actionable. Compaction, tool-call offloading, progressive skill disclosure.

What makes this different (with receipts)
You've seen the pitch: "we route to the best model." Everyone says that. Here's what we actually have:

• GPU infrastructure we own. Not just an API reseller. From GPU placement across clouds to the inference endpoint your agent calls - we control the cost curve.
• A harness-first thesis. We treat agent failures as configuration problems, not model problems. When we moved from a stock harness to our own, completion rates on internal benchmarks improved by 40%+ on the same model.
• Agents.md that earns every line. No brainstormed rules - every constraint in our system prompt traces to a real failure we saw and fixed.

Requirements:

• You've used AI coding agents in anger. Not demos - real work. You have opinions about Claude Code, Codex, OpenCode, Cursor. You know what it feels like when an agent gets stuck and why.
• Strong TypeScript or Go in production. Comfort moving between them. Our surface is TypeScript; our core is Go.
• You think in harness terms. You read "the agent hallucinated" and your first instinct is to ask what context it was missing, what hook should have caught it, what constraint should exist.
• You drive features end-to-end. Design → build → ship → measure → iterate. We don't have layers that absorb ambiguity for you.

Responsibilities:

• Build and evolve the agent harness - ship hooks, permission gates, and context compaction. Every AGENTS.md constraint traces to a failure you personally diagnosed.
• Own long-horizon execution - multi-session task completion via spec-driven prompting, worktree-per-slice git, Ralph loop recovery, and stuck detection. Completion rate is your metric.
• Architect planner/executor/evaluator pipelines - planning with a reasoning model, execution with a fast one, evaluation with a third. No self-verification.
• Manage agent memory and context - state persistence across sessions, context compaction, tool-call offloading. Zero context rot on multi-day work.
• Own the harness surface - CLI, TUI, MCP integrations, sandboxed execution, telemetry. TypeScript on the surface, Go where it matters.

What success looks like (after 6 months):

• You've shipped at least one major harness feature end-to-end: designed it, built it, measured it, iterated.
• You've added constraints to our AGENTS.md based on failures you personally observed and diagnosed.
• You've improved a measurable reliability metric - completion rate, context efficiency, or cost per successful task.
• You've formed strong opinions about where our harness is load-bearing and where it's dead weight.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

This role is designed for a "Hub-and-Spoke" organizational model. The Head of Data will not manage the day-to-day tickets of embedded analysts but will own the Data Strategy, Infrastructure, and Standards that allow those analysts to be successful and consistent across the company.

Role Mission

As the Head of Data, the mission is to transform a decentralized data landscape into a unified, high-performance ecosystem. Head of Data will bridge the gap between autonomous product squads and a centralized data vision. Head of Data is the architect of our data culture, ensuring that while analysts sit within different business units, they operate with a common language, world-class tools, and uncompromised data integrity.

Key Responsibilities

Strategic Leadership & Governance

• Unified Data Strategy: Define and execute a global data roadmap that aligns with company-wide OKRs.
• Standardization: Define universal metrics (e.g., "Active User," "Revenue") to ensure a single source of truth across all departments.
• Data Governance: Set policies for data privacy, security, and compliance (GDPR) without bottlenecking the speed of the product teams.

Platform & Infrastructure

• Modern Data Stack: Own the selection and maintenance of our data warehouse (e.g., Snowflake/Redshift), transformation layers (dbt), and BI tools (Looker/Tableau).
• Data Engineering Oversight: Lead the core data engineering efforts to ensure a robust ETL/ELT pipeline that serves the decentralized "spokes."
• Self-Service Enablement: Build the infrastructure that allows non-technical stakeholders to access insights without needing an analyst for every query.

Functional Excellence & Community

• The Data Guild: Create and lead a "Data Guild" or "Community of Practice" to facilitate knowledge sharing, peer reviews, and mentorship among embedded analysts.
• Talent Bar: Define the hiring standards, leveling rubrics, and career paths for all data roles across the company. 
• Best Practices: Drive the adoption of version control (Git), documentation, and automated testing (Data Quality) within the analytic workflows.

Business Impact & Culture

• Data Literacy: Act as an evangelist for data-driven decision-making, coaching C-suite and Product Leads on how to better leverage data.
• Resource Allocation: Partner with Department Leads to identify where data gaps exist and advocate for the placement of analysts in the highest-impact areas.

Key Requirements

Strategic Leadership & Organizational Design

• Architectural Strategy: 6+ years of experience in Data/Analytics, with a proven track record of scaling "Hub-and-Spoke" or Data Mesh models. Demonstrated ability to balance centralized governance with decentralized execution speed.
• Strategic Influence: Proven ability to influence and align senior stakeholders (C-level, Product Leads) who do not have a direct reporting line to this role. Ability to lead through expertise and professional authority.
• Data-as-a-Product Mindset: A strategic approach to treating the data platform, tooling, and core datasets as internal products, where embedded analysts and business units are the primary customers.
• Change Management: Experience in leading organizational transitions (e.g., from centralized to decentralized) and establishing a high-performance data culture across distributed teams.

Technical Excellence & Methodology

• AI Modernization & Tooling: Lead the evaluation and strategic implementation of cutting-edge AI-driven data extraction solutions, ensuring selected technologies align with cross-departmental requirements and scale seamlessly across the organization’s data infrastructure.
• Modern Data Stack Mastery: Expert-level knowledge of cloud data warehousing (e.g., Snowflake, Redshift), transformation layers (dbt), and orchestration.
• Advanced Analytics & Modeling: Proficiency in SQL and Python/R for complex data modeling and predictive analytics. Deep understanding of version control (Git) and CI/CD practices in data workflows.
• Statistical Rigor & Experimentation: Extensive experience in designing and analyzing A/B tests, causal inference, and applying advanced statistical methods to drive business decisions.
• Operational Intelligence: Background in high-scale operational analytics, including forecasting, capacity planning, efficiency analysis, and automated quality assurance.

Functional Management & Governance

• Talent Development & Bar Raising: Experience in defining hiring standards, career frameworks, and mentorship programs for Data Analysts and Data Scientists.
• Data Governance & Quality: Proven ability to establish global data standards, master data management, and unified metric definitions to ensure a "Single Source of Truth" across the organization.
• Storytelling & Communication: Exceptional ability to translate complex technical findings into persuasive, executive-level narratives that drive operational and strategic improvements.
• Pragmatic Problem Solving: A results-oriented mindset with the ability to bridge the gap between high-level data science and pragmatic, actionable business solutions.

What we believe

At TransferGo, we offer competitive rewards to all people. We know that recognition is about more than just money, and we’ve fostered a culture of kudos to shine a light on the great work throughout the business, and the people making it all happen. We hold regular in-person events to connect with each other and help all our TransferNauts to grow with a generous training allowance. We believe that empowering people makes for a happier and more effective workforce. This means we enable anyone who wants to pursue initiatives that deliver real value for our migrant customers. 

What We Offer:

• Competitive Salary: Starting from 6480-9720€ (gross) per month, depending on experience. Salary is just one part of the conversation – if you’re excited about the role but the range feels slightly off, don’t hesitate to apply. We’re open to discussing based on your experience and potential.
• Comprehensive Benefits: Including a generous holiday allowance, competitive healthcare insurance, and a wellbeing package from day one.
• Annual Development Budget: €1,000 to invest in your personal and professional growth.
• Hybrid Working Environment: Flexibility to work from home and in the office, with most team members in the office two days a week.
• Pet-Friendly Office: If you’re near one of our offices, bring your furry friend along!
• Inclusive Culture: Regular in-person events, fostering a strong sense of community and collaboration.
• Empowerment and Ownership: We believe in empowering our people to take initiative and drive meaningful change.