17Sep

Financial Business Partnering Analyst

Job title: Financial Business Partnering Analyst

Company: ICON

Job description: Financial Business Partnering Analyst – Dublin 18 Hybrid ICON plc is a world-leading healthcare intelligence… and clinical research organization. We’re proud to foster an inclusive environment driving innovation and excellence…

Expected salary:

Location: Dublin

Job date: Sat, 31 Aug 2024 07:30:33 GMT

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17Sep

Design Enablement and Platform Director at Renesas Electronics – Noida, India


Job Description

We are looking for a senior technical leader to drive the Tools/Flows/Methodology, Metric & Dashboard Automation aspects of high-performance compute SOC/MCU development. The candidate must be highly experienced, hands-on and have expert level EDA working knowledge and must have had prior experience in the design enablement, flow development, testing and deployment space. The candidate must have experience working on advance technology nodes and related tape-out experience.

Responsibilities
The successful candidate will be expected to 

  • Be the focal-point to  develop, train & deploy  Chip-Design Methodologies & Workflows to global teams in Renesas
  • Providing the Design Automation support to the SOC & IP development in the tools/flows used for RTL design, Verification, DFT, Physical Design domains.
  • Responsible for internal/external vendor interaction, developing new concepts, methodology and deploying those capabilities to different teams within the organization.
  • Responsible for tools and flows development and support in multiple functional areas including Design Entry solutions, RTL Validation, Functional Coverage, Formal Verification, Low Power solutions, Back-end physical design
  • Continuously improve the process, verification/validation methods and tools, driving the SOC & IP team to achieve successful tape out.
  • Need to work with peers across the business to drive change throughout Renesas to have common methods that work across the whole organization in partnership and collaboration with stakeholders and influence the direction taken.

Involve training program definition and roll out, lessons learned proliferation and best practice sharing.

 

Qualifications

  • Degree in Electrical/Electronic Engineering, Computer Engineering or Computer Science
  • At least 15+ years of experience in related domains and have working knowledge of industry standard digital EDA toolkits to drive the tools/flows certification, regression testing and deployment.
  • Proficiency in Python, TCL, Data Analytics, software workflows.
  • Exeprience & Expsoure to Cloud Infrastructures and ML frameworks
  • Have experience in leading EDA development/design automation and enablement teams in the past.
  • Proven track record in successfully delivering EDA/TFM for multi-million gate, multi-core, Performance/Power optimized, AI/ML enabled, Functionally Safe (ISO 26262) and Secure SOCs.
  • Expertise in all the modern EDA tools and methodologies
  • Strong communication skills (written and verbal), problem solving, teamwork, attention to detail, commitment to task, and quality focus.
  • Passion for continuously improving the SOC development processes, methods, tracking mechanisms, coverage, automation and quality.
  • Presentation and negotiation skills with ability to influence.
  • Strong drive & ability to coordinate work across a cross functional, highly experienced global team.

Additional Information

Renesas Electronics Corporation empowers a safer, smarter and more sustainable future where technology helps make our lives easier. The leading global provider of microcontrollers, Renesas combines our expertise in embedded processing, analog, power and connectivity to deliver complete semiconductor solutions. These Winning Combinations accelerate time to market for automotive, industrial, infrastructure and IoT applications, enabling billions of connected, intelligent devices that enhance the way people work and live. Learn more at www.renesas.com.

Renesas’ mission, To Make Our Lives Easier, is underpinned by our company culture, TAGIE. TAGIE stands for Transparent, Agile, Global, Innovative and Entrepreneurial. Our goal is to embed this unique culture in everything we do to succeed as a company and create trust with our diverse colleagues, customers and stakeholders.

Renesas Electronics is an equal opportunity and affirmative action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement.

Renesas is an embedded semiconductor solution provider driven by its purpose ‘To Make Our Lives Easier.’ As the industry’s leading expert in embedded processing with unmatched quality and system-level know-how, we have evolved to provide scalable and comprehensive semiconductor solutions based on the broadest product portfolio, including High Performance Computing, Embedded Processing, Analog & Connectivity, and Power.  
 
With a diverse team of over 21,000 professionals in more than 30 countries, we continue to expand our boundaries to offer enhanced user experiences through digitalization and usher into a new era of innovation. We remain agile and fearless as we accelerate our growth, encouraging everyone to play an active role with an entrepreneurial mindset and accountability.     
 
At Renesas, you can: 

  • Launch and advance your career in technical and business roles across four Product Groups and various corporate functions. You will have the opportunities to explore our hardware and software capabilities and try new things.  
  • Make a real impact by developing automotive, industrial, infrastructure, IoT, and sustainable products and solutions to meet our customers’ evolving needs and help people and communities thrive tomorrow.  
  • Maximize your performance and wellbeing in our flexible and inclusive work environment. Our people-first culture and global support system, including the remote work option and Employee Resource Groups, will help you excel from Day 1.    
     

Are you ready to own your success and make your mark?  
 

Join Renesas. Let’s Shape the Future together.  

Renesas Electronics is an equal opportunity and affirmative action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement.



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17Sep

Graduate Business Development Associate

Job title: Graduate Business Development Associate

Company: Eurofins

Job description: to develop business from these. Work with group marketing to devise marketing materials and tools to support business… with the business to deliver these improvements. Identification of growth opportunities resulting from quality and services…

Expected salary:

Location: Cork

Job date: Sat, 31 Aug 2024 22:23:58 GMT

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17Sep

Director of GTM Business Analytics

Job title: Director of GTM Business Analytics

Company: WP Engine

Job description: extraordinary WordPress, eCommerce, and headless sites—all thanks to a nonstop commitment to innovation, award-winning WordPress… expertise, and a set of core values that guides us every day. Director of GTM Business Analytics The Director of GTM…

Expected salary:

Location: Limerick

Job date: Sun, 01 Sep 2024 05:16:32 GMT

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17Sep

Premium Hub – CoE: Business Process Consultant – Project Systems, Asset Accounting

Job title: Premium Hub – CoE: Business Process Consultant – Project Systems, Asset Accounting

Company: SAP

Job description: We help the world run better Our company culture is focused on helping our employees enable innovation by building… schedules around business requirements and individual needs. SAP’s employees across different regions are enabled…

Expected salary:

Location: Southside Dublin

Job date: Tue, 03 Sep 2024 22:01:45 GMT

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17Sep

Business Resilience Manager

Job title: Business Resilience Manager

Company: Amgen

Job description: ’s global Lyophilisation centre of excellence. Business Resilience Manager Live What you will do Let’s do this! Let…’s change the world! In this vital role, you will lead the Business Resiliency program for Amgen Dun Laoghaire (ADL). Business

Expected salary:

Location: Dún Laoghaire, Co Dublin

Job date: Tue, 03 Sep 2024 22:05:04 GMT

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17Sep

Graduate Sales & Business Management Trainee

Job title: Graduate Sales & Business Management Trainee

Company: Bridgewater UK

Job description: Are you a recent graduate with a passion for business and the drive to succeed? The UK and Ireland’s largest supplier… of electrical equipment to business and trade customers is offering an exciting opportunity to join their comprehensive graduate…

Expected salary: €32500 per year

Location: Ireland

Job date: Tue, 03 Sep 2024 23:28:08 GMT

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17Sep

Senior Data Governance Practice Lead at Allergan Data Labs – remote


Allergan Data Labs is on a mission to transform the Allergan Aesthetics beauty business at AbbVie, one of the largest pharmaceutical companies in the world. Our iconic brands include BOTOX® Cosmetic, CoolSculpting®, JUVÉDERM® and more. The medical aesthetics business is ripe for rapid growth and disruption, and we are looking to add to our high performing team to do just that. 

Our team has successfully launched a new and innovative technology platform, Allē, which serves millions of consumers, tens of thousands of aesthetics providers and thousands of colleagues throughout the US. Since its launch in November 2020, Allē has delivered curated promotions, personalized experiences and had millions of consumers use it as part of their beauty journey. 

We’re looking to add to our team as we prepare to launch a new array of game-changing technologies on our successfully adopted platform. If you’re interested in working within a startup-oriented environment, while having the backing of a very large company, please read on.

As a Senior Data Governance Practice Lead, you will report to the Director of Data Governance, as well as continuously collaborate with key stakeholders across the business to solve the most important technical problems.

You will be responsible for collaborating with cross functional partners and leading practice and Workstream efforts by applying data governance technologies and develop processes to ensure that our data meets the highest standards for privacy, accuracy, observability, and regulatory requirements. This role requires a blend of authoritative knowledge in data governance, strong technical background and experience in data engineering & architecture, and leadership skills that will inspire collaboration among our partners.

Responsibilities

  • Building upon your strong technical background and experience, you’ll lead with partners to build & integrate technologies for Data Governance and other aspects of data management

  • Champion of Data Governance and guide program leadership to create, maintain, and execute program and Workstream roadmaps

  • Mentor and support other Data Governance Practice Leads across Workstreams

  • Monitor and manage work queues containing data related issues and stewardship activities

  • Create and maintain content and communications describing program progress and capabilities

  • Take ownership for achieving objectives & key results, defining the roadmap, allocating resources, and stepping-in to execute when needed to ensure success

  • Develop process and procedure documentation in support of Data Governance initiatives

  • Create and maintain training materials

  • Present program content and progress as requested

  • Contribute to positive vendor relationships for tools & technologies that achieve federated governance, quality, and observability across multiple domains

  • Provide user technical support and training for Data Governance tools

  • Champion program meetings, Workstream meetings, stewardship forums, and various work session as needed

  • Provide administrative support to program leadership

  • Be agile and aware in flexing across immediate role to assist peers with day-to-day responsibilities

  • Contribute to project management services as needed

  • Conduct continuing industry research and identify best practices to incorporate into the Data Governance program

  • Take ownership for our data being secure, appropriately discoverable & accessible, clearly defined & classified, high quality, and traceable

  • Take responsibility for personal development by seeking training, on-the-job experiences, and input from supervisor and peers

  • Maintain sharp professional knowledge, and stay abreast of new tools and developments in data management, regulatory frameworks, and data technologies

Data Catalog & Glossary Workstream

  • Drive the definition of enterprise metadata requirements, standards, and processes

  • Facilitate the publishing and maintenance of business, technical, and operational metadata

  • Design and implement automated metadata capture and publication where possible

  • Develop and deploy innovative approaches to improving the organization’s data literacy

  • Design and implement inventories for data sources, system interfaces, and the Stewardship Community

Data Quality & Observability Workstream

  • Develop innovative approaches to implement and sustain enterprise data quality capabilities

  • Design and implement a data quality business rule inventory

  • Facilitate data profiling and data classification services

  • Develop control structures within an enterprise environment to ensure the accuracy and quality of data across all critical applications, processes, repositories, reports, extracts, and any other data management process

  • Coordinate the resolution of data quality issues with the Stewardship Community

  • Publish Data Quality scorecards

Data Policies & Workflows Workstream

  • Define data related decision rights & accountabilities

  • Manage an enterprise data regulatory and business sensitive workgroup

  • Draft and implement policies to clarify what employees, contractors, and business associates can and cannot do with data

  • Create and facilitate Data Contracts work leveraging YAML files through source control and UI integration

Data Domains & Data Products Workstream

  • Work with program leadership to define data domains for grouping data assets and to assign data related decision rights and accountabilities

  • Work with program leadership to name domain owners and stewards

  • Work with program leadership to prioritize which data domains to govern and when

Required Experience & Skills

  • Solid understanding of requirements for HIPAA, GDPR, CCPA, PCI DSS, and related regulatory frameworks

  • At least 5 years of experience working on a data engineering, data science & analytics, or software team dealing primarily with data, Data Governance, DataOps, data infrastructure, or similar

  • Experience guiding and leading the integration & operation of multiple data governance tools such as data catalogs, access controls, MDM, provenance, and observability

  • Experience having managed data in a multi-domain enterprise with data products owned by different organizations (as opposed to one monolithic data repository)

  • Strong interpersonal communication skills, relationship building skills, and the ability to influence others through persuasion

  • Because this role will benefit from technical experience to guide decisions:

    • BS, MS, or PhD in Computer Science, Engineering, other quantitative field

    • At least 5 years of prior experience as an individual contributor in data-related roles such as data engineer, data software engineer, data scientist/analyst, DataOps, or similar

    • Experience of data storage architectures such as relational & NoSQL databases, data warehouses, data lakes, and lakehouses

    • Experience & strong understanding of data flow architectures including microservices & APIs, ETL/ELT, streaming, messaging, etc.

    • Strong understanding of Master Data Management approaches & best practices

    • Experience creating and understanding technical artifacts (system design, data models) to a high degree of clarity

  • Ability to work effectively from your remote location using modern collaborative tools running on a company-provided laptop

  • Data querying skills, including SQL

Preferred Experience & Skills

  • Experience setting up or contributing to governance in a data mesh environment across a large enterprise consisting of multiple domains offering data as products

  • Experience in the industries of healthcare or medical technologies

  • Familiarity with the principles & tools of Data Engineering, Data Science, DataOps, MLOps, and BI

  • Understanding of AI and machine learning, especially with regard to how it affects governance, quality, and regulatory requirements

  • Experience integrating 3rd-party data sources from marketplaces, brokers, and other sources

Our Core Values 

  • Be Humble: You’re smart yet always interested in learning from others. 

  • Work Transparently: You always deal in an honest, direct and transparent way. 

  • Take Ownership: You embrace responsibility and find joy in having the answers. 

  • Learn More: Through blog posts, newsletters, podcasts, video tutorials and meetups you regularly self-educate and improve your skill set. 

  • Show Gratitude: You show appreciation and return kindness to those you work with. 

Perks 

  • Competitive salary

  • Competitive annual bonus targets. 

  • 401k with dollar for dollar match, up to 6% of eligible earnings (base, bonus).  Plus additional company contribution. 

  • RSU grants (Long Term Incentives) for approved roles. 

  • Comprehensive medical, dental, vision and life insurance. 

  • 17 paid holidays per year, including 3 floating holidays. 

  • Annual Paid Time Off (PTO), with separate sick days.

  • 12 weeks paid Parental Leave.

  • Caregiver Leave.

  • Adoption and Surrogacy Assistance Plan.

  • Flexible workplace accommodations. 

  • Attend AWS Re:Invent in person (Las Vegas) or virtually each year for approved roles.

  • Tuition reimbursement. 

  • A MacBook Pro and accompanying hardware to do great work. 

  • A modern productivity toolset to get work done: Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more. 

  • Generous discounts on SkinMedica skin care products. 

 

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position.  Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range.  This range may be modified in the future.
  • We offer a comprehensive package of benefits including paid time off. (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
  • This job is eligible to participate in our short-term incentive programs.
  • This job is eligible to participate in our long-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company’s sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.Compensation Range (Minimum – Maximum)$95,500—$181,500 USD

 

 



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17Sep

Premium Hub – CoE: Business Process Consultant – Project Systems, Asset Accounting

Job title: Premium Hub – CoE: Business Process Consultant – Project Systems, Asset Accounting

Company: SAP

Job description: We help the world run better Our company culture is focused on helping our employees enable innovation by building… schedules around business requirements and individual needs. SAP’s employees across different regions are enabled…

Expected salary:

Location: Southside Dublin

Job date: Wed, 04 Sep 2024 00:05:43 GMT

Apply for the job now!

17Sep

An AI Agent Architecture & Framework Is Emerging | by Cobus Greyling | Sep, 2024


We are beginning to see the convergence on fundamental architectural principles that are poised to define the next generation of AI agents…

These architectures are far more than just advanced models — there are definitive building blocks emerging that will enable AI Agents & Agentic Applications to act autonomously, adapt dynamically, and interact and explore seamlessly within digital environments.

And as AI Agents become more capable, builders are converging on the common principles and approaches for core components.

I want to add a caveat: while there’s plenty of futuristic speculation around AI Agents, Agentic Discovery, and Agentic Applications, the insights and comments I share here are grounded in concrete research papers and hands-on experience with prototypes that I’ve either built or forked and tested in my own environment.

But First, Let’s Set The Stage With Some Key Concepts…

At a high level, an AI Agent is a system designed to perform tasks autonomously or semi-autonomously. Considering semi-autonomous for a moment, agents make use of tools to achieve their objective, and a human-in-the-loop can be a tool.

AI Agent tasks can range from a virtual assistant that schedules your appointments, to more complex agents involved in exploring and interacting with digital environments. With regards to digital environments, the most prominent research is from Apple with Ferret-UI, WebVoyager, and research from Microsoft and others; as seen below…

An AI Agent is a program that uses one or more Large Language Models (LLMs) or Foundation Models (FMs) as its backbone, enabling it to operate autonomously.

By decomposing queries, planning & creating a sequence of events, the AI Agent effectively addresses and solves complex problems.

AI Agents can handle highly ambiguous questions by decomposing them through a chain of thought process, similar to human reasoning.

These agents have access to a variety of tools, including programs, APIs, web searches, and more, to perform tasks and find solutions.

Much like how Large language models (LLMs) transformed natural language processing, Large Action Models (LAMs) are poised to revolutionise the way AI agents interact with their environments.

In a recent piece I wrote, I explored the emergence of Large Action Models (LAMs) and their future impact on AI Agents.

Salesforce AI Research open-sourced a number of LAMs, including a Small Action Model.

LAMs are designed to go beyond simple language generation by enabling AI to take meaningful actions in real-world scenarios.

Function calling has become a crucial element in the context of AI Agents, particularly from a model capability standpoint, because it significantly extends the functionality of large language models (LLMs) beyond text generation.

And hence one of the reasons for the advent of Large Action Models which has as one of its main traits the ability to excel at function calling.

AI Agents often need to perform actions based on user input, such as retrieving information, scheduling tasks, or performing computations.

Function calling allows the model to generate parameters for these tasks, enabling the agent to trigger external processes like database queries or API calls.

While LAMs form the action backbone, model orchestration brings together smaller, more specialised language models (SLMs) to assist in niche tasks.

Instead of relying solely on massive, resource-heavy models, agents can utilise these smaller models in tandem, orchestrating them for specific functions — whether that’s summarising data, parsing user commands, or providing insights based on historical context.

Small Language Models are ideal for development and testing, running them in an offline mode locally.

Large Language Models (LLMs) have rapidly gained traction due to several key characteristics that align well with the demands of natural language processing. These characteristics include natural language generation, common-sense reasoning, dialogue and conversation context management, natural language understanding, and the ability to handle unstructured input data. While LLMs are knowledge-intensive and have proven to be powerful tools, they are not without their limitations.

One significant drawback of LLMs is their tendency to hallucinate, meaning they can generate responses that are coherent, contextually accurate, and plausible, yet factually incorrect.

Additionally, LLMs are constrained by the scope of their training data, which has a fixed cut-off date. This means they do not possess ongoing, up-to-date knowledge or specific insights tailored to particular industries, organizations, or companies.

Updating an LLM to address these gaps is not straightforward; it requires fine-tuning the base model, which involves considerable effort in data preparation, costs, and testing. This process introduces a non-transparent, complex approach to data integration within LLMs.

To address these shortcomings, the concept of Retrieval-Augmented Generation (RAG) has been introduced.

RAG helps bridge the gap for Small Language Models (SLMs), supplementing them with the deep, intensive knowledge capabilities they typically lack.

While SLMs inherently manage other key aspects such as language generation and understanding, RAG equips them to perform comparably to their larger counterparts by enhancing their knowledge base.

This makes RAG a critical equalizer in the realm of AI language models, allowing smaller models to function with the robustness of a full-scale LLM.

As AI Agents gain capabilities to explore and interact with digital environments, the integration of vision capabilities with language models becomes crucial.

Projects like Ferret-UI from Apple and WebVoyager are excellent examples of this.

These agents can navigate within their digital surroundings, whether that means identifying elements on a user interface or exploring websites autonomously.

Imagine an AI Agent tasked with setting up an application in a new environment — it would not only read text-based instructions but also recognise UI elements via OCR, mapping bounding boxes and interpreting text to interact with them, and provide visual feedback.

A fundamental shift is happening in how AI agents handle inputs and outputs.

Traditionally, LLMs have operated with unstructured input and generated unstructured output — short to paragraphs of text or responses. But now, with function calling, we are moving toward structured, actionable outputs.

While LLMs are great for understanding and producing unstructured content, LAMs are designed to bridge the gap by turning language into structured, executable actions.

When an AI Agent can structure its output to align with specific functions, it can interact with other systems far more effectively.

For instance, instead of generating a merely unstructured/conversational text response, the AI could call a specific function to book a meeting, send a request, or trigger an API call — all within a more efficient token usage.

Not only does this reduce the overhead of processing unstructured responses, but it also makes interactions between systems more seamless.

Something to realise in terms of Function Calling, is that when using the OpenAI API with function calling, the model does not execute functions directly.

AI Agents can now become truly part of the larger digital ecosystem.

Finally, let’s talk about the importance of tools in the architecture of AI agents.

Tools can be thought of as the mechanisms through which AI Agents interact with the world — whether that’s fetching data, performing calculations, or executing tasks. In many ways, these tools are like pipelines, carrying inputs from one stage to another, transforming them along the way.

What’s even more fascinating is that a tool doesn’t necessarily have to be an algorithm or script. In some cases, the tool can be a human-in-the-loop, where humans intervene at key moments to guide or validate the agent’s actions.

This is particularly valuable in high-stakes environments, such as healthcare or finance, where absolute accuracy is critical.

Tools not only extend the capabilities of AI agents but also serve as the glue that holds various systems together. Whether it’s a human or a digital function, these tools allow AI agents to become more powerful, modular, and context-aware.

As we stand at the cusp of this new era, it’s clear that AI agents are becoming far more sophisticated than we ever anticipated.

With Large Action Models, Model Orchestration, vision-enabled language models, Function Calling, and the critical role of Tools, these agents are active participants in solving problems, exploring digital landscapes, and learning autonomously.

By focusing on these core building blocks, we’re setting the foundation for AI agents that are not just smarter, but more adaptable, efficient, and capable of acting in ways that starts to resemble human problem solving and thought processes.

I’m currently the Chief Evangelist @ Kore AI. I explore & write about all things at the intersection of AI & language; ranging from LLMs, Chatbots, Voicebots, Development Frameworks, Data-Centric latent spaces & more.

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