Cloud Platform Engineer with a focus on Azure and AI automation Job at NTT DATA (Cluj)

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Software Development Advisor - Technical Support Engineer (Azure AI Foundry)

We are currently seeking a Software Development Advisor to join our team in Ciud...

Location

Mexico , Ciudad de Mexico

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

3+ years of experience with Microsoft Azure
2+ years of experience with Azure AI Foundry (mandatory)
2+ years of hands-on experience in Azure Machine Learning (mandatory)
1+ year of practical experience building RAG-based agents and using MCP (Model Context Protocol or similar patterns)
Experience in technical support, cloud operations, or AI/ML support roles
Strong proficiency in Python (mandatory)
Strong proficiency in SQL (mandatory)
Experience working with Azure Machine Learning
Azure AI Foundry core services: Cognitive Services, Azure OpenAI, Azure AI Search, Azure Document Intelligence
Databases and data platforms: Azure Synapse Analytics, SQL-based systems

Job Responsibility

Provide technical support for Azure AI Foundry environments and solutions
Troubleshoot and resolve issues related to Azure AI Foundry services (Cognitive Services, Azure OpenAI, etc.), Azure Machine Learning environments and pipelines, RAG architectures and AI agents, Azure AI Search and Azure Document Intelligence, Data pipelines, integrations, and model inference workflows
Support deployment, configuration, and maintenance of AI solutions in Azure
Analyze logs, metrics, and telemetry to identify root causes and recommend solutions
Collaborate with Engineering, Product, and Cloud Operations teams on escalations
Assist customers with implementation of reference architectures and best practices
Manage support incidents following SLA commitments
Document troubleshooting steps, runbooks, and knowledge base articles
Contribute to continuous improvement by identifying recurring issues
Support CI/CD pipelines and automation of AI workloads

Fulltime

Senior Software Engineer - AI Engineering and Productivity

The Role The AI Engineering and Productivity team in the Global Planning, Desig...

Location

United States , Austin; Warren

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience
6+ years of experience delivering enterprise or full stack software solutions using Java / JEE, Python , and preferably Angular
3+ years of experience working with complex SQL queries, functions, and stored procedures, including performance tuning and optimization against large datasets
Experience building or supporting data pipelines , ETL/ELT processes, or datacentric applications on distributed or cloud platforms (e.g., Databricks, Spark , or similar)
3+ years of experience with Kubernetes/Docker, Quarkus , and cloud platforms such as Azure, AWS , or GCP
Experience working in Agile/SCRUM development methodologies, including backlog refinement, sprint planning, and incremental delivery
Hands on experience with modern DevOps practices such as Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines (e.g., GitHub Actions)
Willingness and demonstrated ability to learn and apply AI concepts , including working with data and APIs that support AI/ML and LLM based solutions
Strong problem solving skills with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high quality solutions
Excellent written and verbal communication skills with the ability to collaborate with both technical and nontechnical stakeholders

Job Responsibility

Design, develop, and maintain data driven and AI-enabled applications and services that support Product Development engineering teams
Write high-quality, performant SQL (queries, functions, stored procedures) for complex data transformations and modeling across enterprise data platforms (e.g., SQL Server, Oracle, PostgreSQL)
Build and optimize data pipelines and workflows in Databricks (DBX) and related tools to support batch and near realtime data processing
Develop backend services and APIs in Java and/or Python that integrate data, business rules, and user workflows into robust, reusable components
Develop enterprise grade applications using Kubernetes/Docker, Quarkus, Java, Angular, PostgreSQL, and other GM approved tools
Partner with data science and AI teams to productionize AI/ML and LLM based solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement
Proactively identify and remediate issues related to code quality, patterns, performance, security, and data correctness, using code quality analysis tools and remediation techniques
Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and Statement of Technical Direction
Apply and champion software engineering best practices, including code reviews, automated testing, branching strategies, CI/CD pipelines (e.g., GitHub Actions), observability, and secure coding practices
Collaborate with cross-functional teams (product owners, data engineers, architects, business stakeholders) to refine requirements, define acceptance criteria, and deliver incremental value in an Agile/SCRUM environment

What we offer

Relocation benefits

Fulltime

Sr. Cloud Infrastructure Engineer (Ai & Llm Platforms)

We are seeking a specialized Infrastructure Engineer to bridge the gap between o...

Location

Salary:

Not provided

Q6 Cyber

Expiration Date

Until further notice

Requirements

5+ years of experience in DevOps, Platform Engineering, or SRE, with at least 1-2 years specifically focused on AI/ML infrastructure
Proven track record of building production-grade RAG pipelines or LLM-integrated applications
Thrives in 'day zero' environments where the tools and protocols (like MCP) are evolving weekly
Deep understanding of the security implications of LLMs (prompt injection, data leakage, and secure tool execution)
Experience working with substantial datasets (over 1bn objects, dozens or hundreds of TBs) and the challenges of leveraging AI tools with these data sets
Bachelor's degree or equivalent in computer science or related field
Cloud & Orchestration: AWS/GCP/Azure, Kubernetes, Terraform, Helm
AI Frameworks: LangChain, LlamaIndex, LangGraph
Data & Vectors: Pinecone, Milvus, Qdrant, or pgvector
Apache Kafka/Pulsar

Job Responsibility

Guide the architecture that will allow us to leverage AI tools with our large existing data stores and incoming streams of realtime intelligence
Work closely with other infrastructure engineers and software development teams to integrate AI tools into existing systems
Design, deploy, and maintain Model Context Protocol (MCP) servers to allow LLMs to securely interact with our internal databases, APIs, and external tooling
Build and orchestrate sandboxed, scalable environments (e.g., using Docker or specialized runtimes) where users can safely build and execute AI agents
Develop and manage the infrastructure for our internal RAG (Retrieval-Augmented Generation) pipeline, including vector database management (e.g., Pinecone, Weaviate, or pgvector) and automated embedding pipelines
Utilize Kubernetes (K8s) and Infrastructure as Code (Terraform/Pulumi) to deploy LLM-related tools, ensuring high availability and low latency for model inference and data retrieval
Implement strict guardrails for data privacy within LLM workflows, ensuring internal datasets remain secure while being accessible to authorized AI tools

What we offer

We offer a competitive compensation package and comprehensive benefits package

Fulltime

Senior and Principal Software Engineers - Azure AI Search

Join Azure AI Search Engineering Foundations as a Senior or Principal Software E...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Experience building or operating services on Azure (or comparable cloud platform).
Experience with secure engineering practices (e.g., threat modeling, secure coding, secrets management, managed identities, authentication/authorization, certificates).
Experience building developer platforms or frameworks (e.g., validation frameworks, test infrastructure, internal SDKs, reusable libraries).
Experience evaluating or integrating AI-assisted developer workflows in a production engineering environment.
Master's Degree in Computer Science or related technical field OR equivalent experience.
Successful track record delivering production software end-to-end (design, implementation, testing, rollout) for a service or platform, with clear ownership of at least one meaningful component or capability.
Successful track record improving engineering productivity through tooling, automation, build/test infrastructure, CI/CD, or operational tooling—demonstrated by measurable outcomes (e.g., reduced build/test/validation time, improved pipeline reliability, reduced manual steps/toil).
Successful track record operating and improving reliability of software systems by diagnosing issues from logs/metrics/traces, driving fixes, and validating improvements (e.g., reduced incident recurrence, improved operational health signals).
Successful cross-team collaboration: partnered with stakeholders to clarify ambiguous requirements, evaluate tradeoffs, and deliver agreed outcomes (e.g., shipped incremental milestones, communicated risks and dependencies clearly).

Job Responsibility

Own and deliver engineering foundations work end‑to‑end—spanning design, implementation, testing, rollout, and iteration—to improve the inner‑ and outer‑loop developer experience across Azure AI Search.
Partner closely with feature, platform, and infrastructure teams to understand developer pain points, translate requirements into pragmatic tooling, automation, and process improvements, and drive adoption through collaboration and iteration.
Prototype, evaluate, and integrate AI‑assisted engineering tools and modern workflows that measurably improve developer productivity, quality, reliability, and operational confidence.
Design and incrementally deliver scalable, reliable, and efficient solutions across CI/CD pipelines, build and test infrastructure, validation frameworks, automation, and operational tooling—using data and feedback to validate impact.
Apply a security‑first mindset in daily engineering work, including secure coding practices, threat modeling, identity and secrets hygiene, and compliance‑aware design.
Navigate ambiguity by breaking down complex problems, proposing options and tradeoffs, aligning stakeholders around a clear direction, and communicating progress, risks, and outcomes effectively.
Lead by example through strong technical judgment, mentorship, and collaboration, helping raise the bar for engineering practices while fostering an inclusive, high‑trust team culture.
Define and influence a high‑quality developer experience for Azure AI Search by setting standards, establishing best practices, and driving improvements that enable engineering teams to thrive.
Deliver results with a focus on measurable outcomes, such as reduced build and test times, faster PR validation, improved pipeline reliability, and decreased manual toil.

Fulltime

Sr Staff ML Engineer - Production & MLOps Focus - GenAI Security Platform

Join our team building a cutting-edge multi-tenanted GenAI Security Platform tha...

Location

India , Bengaluru

Salary:

Not provided

Palo Alto Networks

Expiration Date

Until further notice

Requirements

4+ years of ML engineering experience with hands-on LLM/NLP work
Practical experience building LLM-based applications (agents, multi-turn systems, evaluators)
Understanding of model fine-tuning, embedding optimization, and prompt engineering
Experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI)
Knowledge of LLM orchestration frameworks ( LangChain, LlamaIndex, Pydantic AI, custom solutions)
Familiarity with model architectures and when to fine-tune vs prompt engineer
Strong experience deploying ML models to production at scale
Experience with Model serving frameworks (vLLM preferred
TensorRT-LLM, Ray Serve, or similar a plus)
Kubernetes and Docker proficiency for ML workload orchestration

Job Responsibility

Build and deploy LLM-based agents and multi-step evaluation workflows
Fine-tune models, optimize embeddings, and manage model weights and artifacts
Deploy and scale ML services on Kubernetes with proper monitoring and resource management
Implement experiment tracking, model versioning, and deployment automation
Develop observability dashboards for ML metrics, costs, latency, and quality
Optimize LLM API usage through caching, batching, and intelligent routing strategies
Manage vector database infrastructure and semantic search systems
Create CI/CD pipelines for ML artifacts and automated testing frameworks
Collaborate with ML researchers to productionize prototypes and scale experiments

Fulltime

Senior Machine Learning Engineer (LLMs, MLOps, Computer Vision & Cloud AI)

We are seeking a highly skilled Senior Machine Learning Engineer to design, deve...

Location

United States , Austin

Salary:

Not provided

Dutech Systems

Expiration Date

Until further notice

Requirements

8+ years of experience in cloud platforms including AWS, Azure, GCP, or OCI
8+ years of experience with DevOps technologies including Docker, Kubernetes, Ansible, and CI/CD automation
Strong experience with SQL databases (PostgreSQL, MySQL) and NoSQL/vector databases
Proficiency in Bash and PowerShell scripting for automation and infrastructure management
Experience with Azure DevOps, GitHub Actions, Jenkins, or similar CI/CD platforms
3+ years of hands-on Python development experience in production environments
3+ years of experience with NLP, LLMs, transformers, prompt engineering, RAG, and AI application development
Experience building and deploying machine learning models serving real-world users
Experience with time-series forecasting, anomaly detection, and predictive analytics
Experience developing recommendation systems and personalization engines

Job Responsibility

Design, develop, deploy, and maintain production-grade machine learning and AI solutions
Build and optimize Large Language Model (LLM) applications using GPT, BERT, T5, Hugging Face, Ollama, and similar technologies
Develop Retrieval-Augmented Generation (RAG) systems, prompt engineering strategies, and fine-tuning workflows
Implement and maintain MLOps pipelines using MLflow, Kubeflow, Airflow, Weights & Biases, or similar tools
Deploy and manage AI workloads across AWS, Azure, GCP, and OCI cloud environments
Design and support scalable infrastructure using Docker, Kubernetes, Ansible, and CI/CD pipelines
Develop machine learning models for forecasting, anomaly detection, predictive analytics, and real-time monitoring
Build recommendation engines, personalization platforms, ranking systems, and collaborative filtering solutions
Develop and deploy computer vision solutions using PyTorch, TensorFlow, OpenCV, YOLO, object detection, and image segmentation techniques
Implement feature engineering strategies and feature stores such as Feast or Tecton

Fulltime

New

Director, Predictive Analytics and AI

Join Takeda as a Director, Predictive Analytics and AI out of our Cambridge, MA ...

Location

United States , Cambridge

Salary:

177000.00 - 278080.00 USD / Year

BioLife Plasma Services

Expiration Date

Until further notice

Requirements

Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, Economics or a related field required
10+ years of hands-on experience in AI/ML modeling, with at least 5 years in pharmaceutical commercial analytics required
Prior people management experience required
Strong technical expertise in machine learning, NLP, and recommendation systems
Experience with pharma data (e.g., IQVIA, Veeva, SP & claims) and strong understanding of compliance and privacy considerations
Proficiency in Artificial Intelligence, with demonstrated expertise in establishing GenAI (Generative AI) and Agentic AI methodologies and solutions
Proficient in Data Science tools and languages such as Python, R, SQL, Databricks, and is familiar with cloud platforms (AWS, Azure, GCP)
Expert in delivering persuasive presentations, conveying complex advanced Data Science driven insights to non-technical audience, and mentoring others in presentation skills
Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams
Strong project management skills, with the ability to manage multiple projects simultaneously

Job Responsibility

Advance Data Science and AI capabilities driving the utilization of predictive models in areas including Patient finding, HCP Targeting and Prioritization, Next Best Action Engines, predictive secondary data driven Patient and predictive Customer Segmentations
Advance Predictive Analytics for US. GI, NS, PDT, and Rare Disease Franchises, including new product launches or indications
Partner with BUs, BU Analytics & Insights, Marketing and Sales Ops, Data CoEs etc.to define use cases and integrate predictive model-driven decisioning into business decisions
Strategic Leadership: Develop and execute a future-oriented data science strategy for commercialization, focusing on leveraging predictive and machine learning models to solve complex business challenges
Predictive Modeling & AI Innovation: Design and deploy predictive models—including logistic regression, ensemble methods, and other machine learning algorithms—for key applications such as trialist identification, patient segmentation, next-best-action (NBA), and HCP target prioritization. Lead the development of AI/ML algorithms to predict patient events, identify undiagnosed / misdiagnosed patients to drive targeted HCP engagements. Create scalable, reusable frameworks for AI and machine learning experimentation and deployment across multiple therapeutic areas
Cross-Functional Partnership: Collaborate as a key thought partner with cross-functional teams—including Business Units, Brand Insights & Analytics, Marketing & Sales Operations, Patient Services, and Medical Affairs—to drive business impact. Develop creative strategies to ensemble multiple third-party patient data sets, enhancing coverage and precision in patient identification and predictive segmentations
Mentor and develop talent: Cultivate a high-performing team of data scientists by promoting continuous learning and encouraging the adoption of emerging AI techniques, ensuring a culture of innovation and excellence. Promote ongoing AI skill development through hands-on training, external partnerships, and internal knowledge sharing
GenAI and Agentic AI Initiatives: Establish and lead GenAI and Agentic AI initiatives that are strategically aligned with CA&I goals. Drive the adoption and integration of advanced AI technologies to enhance analytics capabilities, automate insights generation, and support innovative commercial strategies
Innovation & Continuous Improvement: Continually evolve analytical methods, platforms, standards, and toolsets to meet current and future business needs. Lead Data Science team efforts in developing advanced analytic and AI models providing continuous insights into execution optimization, and industry developments
Strategic Consultation & Stakeholder Engagement: Act as a trusted thought partner to franchise Analytics & Insights, forecasting, and Patient Diagnosis Heads - leading data science driven discussions and translating business needs into appropriate predictive modeling strategies

What we offer

short-term and/ or long-term incentives
medical, dental, vision insurance
401(k) plan and company match
short-term and long-term disability coverage
basic life insurance
tuition reimbursement program
paid volunteer time off
company holidays
well-being benefits
up to 80 hours of sick time per calendar year

Fulltime

Lead Agentic Ai Engineer

Citi's Wholesale Technology organization is seeking an exceptional, hands-on Lea...

Location

Canada , Mississauga

Salary:

120800.00 - 170800.00 USD / Year

Citi

Expiration Date

Until further notice

Requirements

6–10 years of relevant experience in an AI/ML development role, Applications Development, or Systems Analysis, with a substantial and demonstrated focus on Python technologies
Minimum 2+ years of professional experience in software development with a focus on AI, prompt engineering, machine learning, and/or agentic AI systems
Proven track record as a lead developer for agentic flow design, prompt design, and testing of autonomous AI systems with deep expertise in Google ADK
Subject Matter Expert (SME) in at least one area of Applications Development, particularly Python application development (Django, Flask, FastAPI)
Python (expert-level): FastAPI, Django, Flask, asyncio, PySpark — strong fundamentals in algorithms, data structures, concurrency, and design patterns
Proficient in Java (Spring Boot, Spring Cloud), JavaScript/TypeScript (React, Next.js, Node.js), and SQL/data modeling
Experience across AWS, Azure, and GCP with Docker, Kubernetes, and CI/CD pipelines
Proficient in MLOps practices including model versioning, deployment, and lifecycle management
Strong foundation in secure API design, microservices, event-driven architecture, and distributed systems with expertise in testing, Git workflows, and performance optimization
Deep expertise in LLMs (OpenAI GPT, Gemini, Claude, Llama) with hands-on experience in LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, and Google ADK

Job Responsibility

Lead end-to-end design, development, and deployment of large-scale agentic AI solutions using Google Agent Development Kit (ADK) and frameworks such as LangChain, LangGraph
Architect advanced multi-agent systems (perception, reasoning, planning, execution) integrating multiple LLM providers (OpenAI, Anthropic, Google Gemini)
Build AI-powered capabilities using Google Gemini, Vertex AI, Agent Development Kit (ADK), Google A2UI, vector databases, RAG pipelines, semantic search, and advanced prompt and context management
Engineer autonomous agents incorporating planning, tool usage, memory management, and multi-step reasoning patterns
Develop scalable, high-performance backend services in Python (FastAPI, asyncio) with resilient APIs, event-driven designs, and microservices architectures
Build and maintain robust data pipelines working with SQL (Oracle, PostgreSQL) and NoSQL (MongoDB) databases
Implement secure REST APIs and agent interfaces with strong authentication, authorization (OAuth), and encryption best practices
Optimize AI agent performance, latency, and cost through prompt optimization, caching strategies, and vector index tuning
Provide architectural guidance for Next-Generation AI (NGAI) initiatives, ensuring adherence to CTO guidelines and platform standards
Develop and maintain a strategic roadmap for generative AI adoption, evaluating new models, techniques, and platforms

Fulltime

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Cloud Platform Engineer with a focus on Azure and AI automation

Job Description

Job Responsibility

Requirements

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