Principal AI Ops Architect Job at Scale (Doha)

Principal Engineer

The Principal AI/ML Operations Engineer leads the architecture, automation, and ...

Location

United States , Pleasanton, California

Salary:

251000.00 - 314500.00 USD / Year

BlackLine

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field
10+ years in ML infrastructure, DevOps, and software system architecture
4+ years in leading MLOps or AI Ops platforms
Strong programming skills in languages such as Python, Java, or Scala
Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow)
Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure)
Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management
Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation
Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking
Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads

Job Responsibility

Define enterprise-level standards and reference architectures for ML-Ops and AIOps systems
Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs)
Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments
Lead incident response and reliability strategies for ML/AI systems
Lead the deployment of AI models and systems in various environments
Collaborate with development teams to integrate AI solutions into existing workflows and applications
Ensure seamless integration with different platforms and technologies
Define and manage MCP Registry for agentic component onboarding, lifecycle versioning, and dependency governance
Build CI/CD pipelines automating LLM agent deployment, policy validation, and prompt evaluation of workflows
Develop and operationalize experimentation frameworks for agent evaluations, scenario regression, and performance analytics

What we offer

short-term and long-term incentive programs
robust offering of benefit and wellness plans

Fulltime

Senior Principal Technical Program Manager - ML Platform

Location

Salary:

231300.00 - 301975.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

8+ years of experience on software teams as Development Manager, Technical Product Manager or TPM leading technical platforms areas
Deep domain experience in AI and/or Search. Example: Model Inference, Model Evaluation, Model Training, LLM Ops, Semantic Search, Search Relevance, etc.
Partner with Engineering in defining direction, strategy and execution at Platform level
Strategic thinking and ability to understand business objectives to translate them into technical problems and programs.
Technical understanding of systems involved. Willingness to develop domain expertise in the area they operate - storage, networking, authentication, capacity management, service deployments, etc.
TPMs are not expected to write or read code, but are expected to understand system flows, block architectures, APIs and such.
Experience defining and running end-to-end complex technical programs
Strong leadership, organizational, and communication skills

Job Responsibility

Understand and stay up-to-date on latest innovations in AI and Search. Partner closely with engineering teams to translate these into practical platform evolution for Atlassian bringing value to our customers.
Analyze business objectives, customer needs, product adoption inhibitors and opportunities, industry trends, and based on these, in close collaboration with your stakeholders, define a long-term strategy and roadmap for your platform and product components.
Understand business objectives and translate them into technical systems problems that need to be prioritized solved in the current business environment.
Define specific systems programs and create a plan of action for realizing those programs. Such programs could be around capacity planning, migration efforts, high availability, network architecture, performance optimization, reliability improvements and more.
Use your technical understanding of Atlassian and related systems to partner with and influence engineers and architects in making progress on these problems.
Responsible for taking a systematic approach to engineering problems. This includes: prioritizing tasks, scoping out the project, defining objectives, and making consistent progress against each of these.
Be accountable for the success of these technical programs by managing the entire lifecycle from initiation to forecasting, budgeting, scheduling, etc.
Manage complex dependencies and projects with a broad scope across the company

What we offer

health and wellbeing resources
paid volunteer days

Business Systems Architect Principal

The Business Systems Architect Principal is central to BT International’s transf...

Location

Hungary , Budapest

Salary:

Not provided

Plusnet

Expiration Date

Until further notice

Requirements

Strategic Architecture Leadership – Proven ability to define and communicate architectural vision for complex business systems landscapes, with track record driving large-scale transformation programmes in regulated telco environments
Business Systems Domain Expertise – Deep understanding of BAU systems (sales, service, enterprise applications) and service operations platforms (service desk, AI Ops, lead-to-cash, billing, inventory) with knowledge of how these capabilities support business operations and cost optimisation
Systems Integration – Extensive experience linking together various IT systems, services and software across BAU applications, service operations platforms and NaaS capabilities to enable functional operation and support business processes
Vendor and Stakeholder Management – Strong ability to work with SaaS platforms and enterprise vendors as strategic partners, negotiate technical implementations and manage complex stakeholder relationships across business and operational teams
Modernisation Patterns – Expert knowledge of incremental modernisation approaches including service operations automation, AI-driven process optimisation and cloud-native patterns that balance operational continuity with transformation
Technical Depth – Hands-on background in business systems integration and service operations with coding capability, enabling credibility with engineering teams and active participation in technical spikes when needed
Operational Excellence – Understanding of comprehensive observability, service resilience and operational automation approaches including metrics, logging, distributed tracing and telemetry pipelines for business systems
NaaS Integration Understanding – Knowledge of how BAU systems integrate with network-as-a-service models, enabling sales and service operations to leverage aaS capabilities whilst maintaining operational stability
Leadership and Influence – Ability to lead blended IT teams (support, maintenance, BAU systems, service operations) through transformation, build consensus across organisational boundaries and develop technical leadership capability in operational functions
Extensive experience leading IT systems and BSS architecture in telecommunications or complex B2B environments, with demonstrated success modernizing legacy landscapes across multiple system domains

Job Responsibility

Define and lead the architectural strategy for business systems across BAU applications (sales, service, enterprise) and service operations (AI Ops, Service Desk, L2C including Pricing/Design/Quoting/SRM, billing, inventory), establishing target state architecture that optimises legacy systems whilst designing future-ready capabilities
Own the business systems portfolio optimisation roadmap, making strategic keep/modernise/retire decisions for BAU systems and service operations platforms based on technical fitness, cost-effectiveness and alignment with asset-light, NaaS-based operating model
Establish systems integration approaches that link together BAU applications, service operations platforms and NaaS capabilities, enabling functional operation across sales, service and enterprise systems whilst supporting business processes
Lead vendor strategy for business systems platforms including SaaS applications, enterprise systems and service operations tools, negotiating strategic partnerships that simplify IT landscape whilst aligning with aaS business needs and reducing vendor dependencies
Champion modern architecture patterns including service operations automation, AI-driven process optimisation, billing automation, inventory accuracy improvement and self-service capabilities that reduce manual propensity and improve cost-to-serve metrics
Design for operational excellence by establishing comprehensive observability across business systems including metrics, logging, distributed tracing and telemetry that enable proactive issue detection and support continuous improvement in service delivery
Collaborate with Data and AI architects to leverage data platforms and AI capabilities for business intelligence, service automation and customer insights, ensuring business systems generate valuable data and support AI-driven process improvements
Drive architectural governance through design reviews and architecture conformance processes, ensuring business systems initiatives align with enterprise standards, security requirements and support transformation to asset-light operating model
Build and mentor Business Systems architects who work with BAU operations and service delivery teams, establishing technical leadership capability and fostering architectural thinking across support, maintenance and enterprise systems functions
Work with engineering leadership to establish integration patterns that connect business systems with NaaS capabilities, enabling sales and service operations to leverage network-as-a-service whilst maintaining operational stability and cost-effectiveness

What we offer

Cafeteria package - HUF 600,000/ year
Performance-based bonus
Comprehensive private health care package for all the employees, which can be extended to family members
Nursery support for mothers returning from maternity
Extended paternity leave: 10+10 day fully paid days
Commuting allowance
Home office allowance
Employee discount opportunities
Highly affordable mobile packages for the family as well
New high-class offices both in Budapest and Debrecen

Fulltime

Full Stack AI Engineer

We are seeking a highly skilled Full Stack AI Engineer to join our team and work...

Location

India , Vadodara;Ahmedabad;Indore

Salary:

Not provided

Prakash Software Solutions Pvt. Ltd

Expiration Date

Until further notice

Requirements

8-10 years of experience in software engineering with a strong focus on AI/ML
Proficiency in frontend frameworks like React, Angular, or Vue.js
Strong hands-on experience with backend technologies like Node.js, Python (with frameworks like Flask, Django, or FastAPI), or Java
Experience with cloud platforms such as AWS, Azure, or GCP
Proven ability to design and implement complex, scalable, and maintainable architectures
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
Passion for continuous learning and staying up to date with the latest advancements in AI/ML
End-to-end experience with at least one full AI stack on Azure, AWS, or GCP, including components such as Azure Machine Learning, AWS SageMaker, or Google AI Platform
Hands-on experience with agent frameworks like Autogen, AWS Agent Framework, LangGraph etc.

Job Responsibility

Collaborate with the Principal Architect to design and implement AI agents and multi-agent frameworks
Develop and maintain robust, scalable, and maintainable microservices architectures
Ensure seamless integration of AI agents , MCP Servers with core systems and databases
Develop APIs and SDKs for internal and external consumption
Work closely with data scientists to fine-tune and optimize LLMs for specific tasks and domains
Implement ML Ops practices, including CI/CD pipelines, model versioning, and experiment tracking
Design and implement comprehensive monitoring and observability solutions to track model performance, identify anomalies, and ensure system stability
Utilize containerization technologies such as Docker and Kubernetes for efficient deployment and scaling of applications
Leverage cloud platforms such as AWS, Azure, or GCP for infrastructure and services
Design and implement data pipelines for efficient data ingestion, transformation, and storage

Fulltime

Principal ML Ops Engineer

Principal ML Ops Engineer who will lead the design and operationalization of ML ...

Location

United States , Charlotte; Phoenix; Johnston; Westwood; Iselin; Boston

Salary:

175000.00 - 230000.00 USD / Year

Citizens Bank

Expiration Date

Until further notice

Requirements

7+ years of experience with Python for scripting ML workflows
5+ years of experience deploying ML pipelines and systems using AWS SageMaker
3+ years of experience developing APIs with Flask, Django, or FastAPI
2+ years of experience with ML frameworks and tools such as scikit-learn, PyTorch, XGBoost, LightGBM, MLflow
Solid understanding of the ML lifecycle: model development, training, validation, deployment, and monitoring
Solid understanding of CI/CD pipelines for ML workflows using Bitbucket, Jenkins, Nexus
Experience with ETL processes for ML pipelines using Spark and Kafka
Bachelor’s Degree or equivalent combination of education, training, and experience required

Job Responsibility

Lead and mentor engineering teams, including GCC talent development and potential onshore leadership
Architect, design, and build ML engineering systems on the CFG ML Platform to accelerate ML pipeline delivery
Develop and enhance platform capabilities and frameworks to standardize and automate ML pipeline deployment
Implement capabilities such as feature stores, feature tracking, feature serving (real-time and batch), model performance monitoring, model lineage tracking, model health, and model serving and consumption (real-time, batch, event-triggered, near real-time using Kafka)
Define processes, research market trends, and implement best practices for ML pipeline development and deployment
Collaborate with business teams, data science teams, enterprise architects, and security to uphold ML engineering standards
Develop CI/CD pipelines for continuous integration and delivery of ML models
Identify and automate ML pipeline and model deployment patterns to streamline workflows
Troubleshoot and resolve issues related to ML system performance and deployment
Contribute to GenAI initiatives, including building intelligent agents and integrating them into ML Ops workflows

What we offer

comprehensive medical, dental and vision coverage
retirement benefits
maternity/paternity leave
flexible work arrangements
education reimbursement
wellness programs
competitive pay
opportunity to earn an annual discretionary bonus

Fulltime

Principal Engineer, Model Dev Platform

As the Principal Engineer for the Model Development Platform at Wayve, you will ...

Location

United States , Sunnyvale

Salary:

Not provided

Wayve

Expiration Date

Until further notice

Requirements

Technical Leadership at Scale – 10+ years of experience designing and building large-scale distributed systems, ML/AI infrastructure, full stack web application, or developer platforms, including at least 3 years as a staff or principal-level engineer
Architectural Depth & Breadth – Proven ability to design systems spanning web platforms, ML pipelines, and large-scale compute orchestration (e.g., Spark, Ray, Kubernetes, Airflow, MLflow)
Reliability & Performance Mindset – Experience driving platform reliability improvements, defining SLAs/SLOs, and building self-healing and observable systems that operate at “four nines” availability or better
Hands-On Systems Design – Deep understanding of distributed computing, workflow orchestration, data modeling, and API design, with the ability to write and review production-quality code
Collaborative Influence – Excellent communication and cross-functional collaboration skills
ability to guide engineers, managers, and researchers toward unified technical direction
Mentorship & Culture – Demonstrated success in mentoring engineers across levels and cultivating a culture of engineering excellence
Education – Bachelor’s degree in Computer Science, Software Engineering, or related field (advanced degree preferred, or equivalent experience)

Job Responsibility

Design and evolve the overarching architecture of the model development platform, ensuring system-wide reliability, observability, and scalability
Work across disciplines—from front-end web UIs to large-scale distributed training, from Spark-based data pipelines to experiment scheduling algorithms using linear optimization—to unify the platform’s architecture and ensure smooth interoperability between systems
Dive deep into the thorniest technical challenges faced by individual subteams, bringing your expertise in distributed systems, large-scale compute, and system design to bear
Develop and refine systems that optimize how models are tested—whether in simulation or on-road—balancing constraints like hardware availability, safety requirements, and research priorities
Architect data processing pipelines capable of ingesting, transforming, and enriching petabytes of sensor data from the global fleet
Serve as a mentor and coach for engineers across the organization—developing technical talent, improving design practices, and fostering a culture of learning and technical excellence
Partner with Product Management, Research, and Operations to align technical architecture with user needs and product vision

Senior Principal, Machine Learning & Artificial Intelligence

Xometry is seeking a Senior Principal, Machine Learning & Artificial Intelligenc...

Location

United States , North Bethesda

Salary:

150000.00 - 196000.00 USD / Year

Cherry Ventures

Expiration Date

Until further notice

Requirements

Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering or related field (PhD preferred for deep generative/3D modeling emphasis)
12+ years of professional experience in machine learning, artificial intelligence, or data science roles — with several years in senior or principal capacity leading major programs
Demonstrated experience architecting and delivering large scale ML/AI solutions - end-to-end from data ingestion, feature engineering, model training, evaluation, deployment, monitoring & operations
Deep expertise in machine learning frameworks (TensorFlow, PyTorch), data engineering, model infrastructure, MLOps, cloud platforms (AWS, GCP, Azure), and scalable production systems
Strong exposure to generative AI techniques (large language models, multimodal models, diffusion, GANs) and translating them into business use-cases
Excellent cross-functional collaboration skills: you can partner with product, engineering, ops, manufacturing, design, business leadership and translate technical concepts into business language
Proven ability to influence without direct authority and drive change across organizations
Strong communication and presentation skills
you can articulate technical vision, roadmap, trade-offs and outcomes to senior leadership
Track record of identifying and delivering measurable business impact via ML/AI - e.g., revenue growth, cost savings, improved efficiency

Job Responsibility

Serve as the technical leader of multiple large, cross-functional ML/AI solutions with significant, lasting impact across Xometry’s business
Define, and drive the 18-24-month ML/AI technical roadmap - balancing breakthrough innovation (e.g., generative 3D, foundation models, large-scale vision/3D pipelines) with reliable business value delivery (e.g., quoting accuracy, lead-time reduction, defect detection, cost optimization)
Influence partner roadmaps across engineering, product, operations, and business teams: align priorities, advise on resourcing, champion ML/AI best practices
Proactively identify and remove roadblocks for teams and projects — whether technical, operational, data-related, or resource constraints
Mentorship of individuals and technical teams
Act as a trusted SME with strong cross-functional partnerships: your insights and guidance will shape ML/AI infrastructure, data, model, infrastructure, and tooling decisions
Play a leadership role in identifying areas of opportunity — e.g., using ML/AI to unlock new revenue streams (e.g., rapid quoting for new manufacturing modalities, generative design for customers), reduce cost (e.g., automated quality inspection), or optimize efficiency (e.g., 3D-geometry classification, defect detection, generating manufacturing ready models)
Address problems adjacent to your sphere of immediate influence: proactively tackle challenges outside direct scope and champion holistic solutions
Stay ahead of industry developments in ML, AI, generative AI, 2D/3D modeling and manufacturing tech
translate insights into the improvement of internal best practices, tooling, frameworks, model governance, data pipelines, and operationalization

What we offer

annual bonus
401(k) match
medical, dental and vision insurance
life and disability insurance
generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave
EAP, other wellbeing resources

Fulltime

Senior Principal, Machine Learning & Artificial Intelligence

Xometry is seeking a Senior Principal, Machine Learning & Artificial Intelligenc...

Location

United States , Waltham

Salary:

150000.00 - 196000.00 USD / Year

Cherry Ventures

Expiration Date

Until further notice

Requirements

Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering or related field (PhD preferred for deep generative/3D modeling emphasis)
12+ years of professional experience in machine learning, artificial intelligence, or data science roles — with several years in senior or principal capacity leading major programs
Demonstrated experience architecting and delivering large scale ML/AI solutions - end-to-end from data ingestion, feature engineering, model training, evaluation, deployment, monitoring & operations
Deep expertise in machine learning frameworks (TensorFlow, PyTorch), data engineering, model infrastructure, MLOps, cloud platforms (AWS, GCP, Azure), and scalable production systems
Experience in 3D modeling / geometry / computer vision / generative models (e.g., point-cloud processing, mesh processing, text23D, image23D, CAD/CAM integration) is highly desirable
Strong exposure to generative AI techniques (large language models, multimodal models, diffusion, GANs) and translating them into business use-cases
Excellent cross-functional collaboration skills: you can partner with product, engineering, ops, manufacturing, design, business leadership and translate technical concepts into business language
Proven ability to influence without direct authority and drive change across organizations
Strong communication and presentation skills
you can articulate technical vision, roadmap, trade-offs and outcomes to senior leadership

Job Responsibility

Serve as the technical leader of multiple large, cross-functional ML/AI solutions with significant, lasting impact across Xometry’s business
Define, and drive the 18-24-month ML/AI technical roadmap - balancing breakthrough innovation (e.g., generative 3D, foundation models, large-scale vision/3D pipelines) with reliable business value delivery (e.g., quoting accuracy, lead-time reduction, defect detection, cost optimization)
Influence partner roadmaps across engineering, product, operations, and business teams: align priorities, advise on resourcing, champion ML/AI best practices
Proactively identify and remove roadblocks for teams and projects — whether technical, operational, data-related, or resource constraints
Mentorship of individuals and technical teams
Act as a trusted SME with strong cross-functional partnerships: your insights and guidance will shape ML/AI infrastructure, data, model, infrastructure, and tooling decisions
Play a leadership role in identifying areas of opportunity — e.g., using ML/AI to unlock new revenue streams (e.g., rapid quoting for new manufacturing modalities, generative design for customers), reduce cost (e.g., automated quality inspection), or optimize efficiency (e.g., 3D-geometry classification, defect detection, generating manufacturing ready models)
Address problems adjacent to your sphere of immediate influence: proactively tackle challenges outside direct scope and champion holistic solutions
Stay ahead of industry developments in ML, AI, generative AI, 2D/3D modeling and manufacturing tech
translate insights into the improvement of internal best practices, tooling, frameworks, model governance, data pipelines, and operationalization

What we offer

401(k) match
medical, dental and vision insurance
life and disability insurance
generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave
EAP, other wellbeing resources

Fulltime

Principal AI Ops Architect

Scale

Location:
Qatar; United Kingdom , Doha ▼
London

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
March 20, 2026

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