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As Manager, Technical Writer (Individual Contributor), you will serve as the senior technical writing expert within the AI Architecture &amp; Solution Design department. Your mission is to define and uphold documentation standards and structure for SDKs, modules, and solution patterns, ensuring clarity, consistency, and discoverability across all artefacts. You will work closely with AI Architects, Solution Designers, and Operations Excellence to make documentation a first-class enabler of adoption and reuse.You will lead by expertise, not direct management—acting as the bar-raiser for technical writing quality and mentoring junior writers informally. Beyond documentation, you will contribute to knowledge surfacing and enablement, including indexing solution patterns and supporting tools (e.g., intelligent agents) that help teams find the right SDK or design quickly. You will also play a supporting role in operations feedback, ensuring documentation standards enable operationalizing the SDK and AI Solution patterns across Creation Centers and digital teams.Why this Role MattersDocumentation is the gateway to adoption and reuse. Without clear, indexed, and actionable artefacts, even the best AI capabilities and solution patterns fail to scale. This role ensures that every SDK, module, and architecture pattern is discoverable, understandable, and implementable, reducing bespoke engineering and accelerating time to value.ROLE RESPONSIBILITIES1) Documentation Standards &amp; Structure<ul><li>Define and maintain documentation standards for SDKs, modules, and solution patterns, including required sections (overview, usage, integration steps, evaluation notes, security/privacy considerations).</li><li>Establish and enforce Confluence structure for indexing and surfacing artefacts; ensure logical hierarchy, tagging, and cross-linking for easy navigation.</li><li>Create templates and style guides for architecture artefacts, release notes, and design exemplars; ensure consistency across teams.</li></ul>2) SDK &amp; Module Documentation<ul><li>Partner with Enterprise AI Capability Design Team and community contributors to produce clear, developer-friendly documentation for SDKs and modules.</li><li>Ensure documentation includes code samples, quickstarts, integration guides, and troubleshooting tips; maintain parity between SDK and service documentation.</li><li>Validate documentation completeness during release readiness checks; track gaps and drive remediation.</li></ul>3) Solution Pattern Indexing &amp; Enablement<ul><li>Curate and document solution patterns with supporting material on “when, why, and how” to use them; collaborate with Solution Designers and AI Architects for accuracy.</li><li>Build and maintain a searchable index of patterns and exemplars; ensure discoverability across Confluence and internal portals.</li><li>Contribute to enablement tools (e.g., intelligent agents) that recommend patterns and modules based on user needs, linking back to documentation and design artefacts.</li></ul>4) Operational Feedback &amp; Continuous Improvement<ul><li>Support operations management activities: observe how documentation standards are applied by Creation Centers and digital teams; capture feedback and propose improvements.</li><li>Participate in retrospectives and process reviews; adjust documentation structure and templates to maximize adoption and usability.</li><li>Ensure documentation supports auditability for compliance, security, and governance requirements.</li></ul>5) Informal Mentorship &amp; Expertise<ul><li>Act as the senior technical writing authority; mentor junior writers informally and provide guidance on complex documentation challenges.</li><li>Promote knowledge sharing and best practices across the department; run documentation clinics and learning sessions.</li></ul>MEASURES OF SUCCESS<ul><li>Documentation completeness and quality: SDKs/modules and solution patterns meet standards; fewer gaps at release readiness.</li><li>Discoverability and adoption: Increased usage of indexed patterns and SDK documentation; positive feedback from consuming teams.</li><li>Operational alignment: Documentation standards consistently applied across Creation Centers; feedback loop drives continuous improvement.</li><li>Enablement impact: Intelligent tools and indexing reduce time to find relevant patterns and modules.</li></ul>QUALIFICATIONSBasic Qualifications<ul><li>5+ years in technical writing or documentation roles within software development environments.</li><li>Proven ability to define and enforce documentation standards and structures for complex technical artefacts.</li><li>Strong familiarity with software development lifecycle, APIs, SDKs, and integration patterns; ability to translate technical concepts into clear, actionable content.</li><li>Ability to interpret system diagrams (Data Flow, Sequence Diagrams) and translate them into clear documentation</li><li>Excellent communication and organizational skills; adept at managing multiple priorities and stakeholders.</li></ul>Preferred Qualifications<ul><li>Experience with AI/ML or GenAI projects; understanding of common patterns (RAG, agentic workflows, evaluation frameworks).</li><li>Hands-on experience with Confluence or similar knowledge management platforms; ability to design logical structures and indexing strategies.</li><li>Background in software engineering (as a developer or technical contributor) is a strong plus.</li><li>Familiarity with CI/CD pipelines, version control, and release documentation practices.</li><li>Experience with markup languages (Markdown) and API documentation standards (OpenAPI/Swagger) is a plus</li><li>Exposure to regulated environments (healthcare, pharma, finance) and audit-ready documentation standards.</li></ul>

Manager, Technical Writer 4949154

The Director, AI Quality Engineering Lead ensures that AI systems across the enterprise are safe, fair, reliable, compliant, and observable from pre‑release through continuous operations. This role designs and operates enterprise evaluation frameworks (quality, bias/fairness, robustness, privacy), leads red‑teaming and guardrail development, encodes policy and regulatory requirements as automated checks, and drives metric reporting and post‑incident learning across AI programs. The lead partners closely with Enterprise Architecture, Compliance, Legal/Privacy, Security, Data Governance, and product/engineering teams to enforce quality and safety gates and enable responsible scale. (Aligned to Corporate Policy and Responsible AI principles.) Reporting into the Head of Applied AI Engineering, you will manage a team of QA Engineers and AI Engineers. This role blends deep technical leadership, product engineering strategy, and direct enablement of enterprise use cases and services. You will partner closely with business, legal and technical stakeholders to design and deliver robust, scalable solutions that demonstrate the value of AI across our enterprise in a safe and compliant way. This role is execution-oriented with strong influence on building AI solutions responsibly.Evaluation and Test Strategy<ul><li>Define and run evaluation frameworks for LLMs and multi-modal systems covering performance, fairness, bias, robustness, safety, and privacy.</li><li>Build automatic + human-in-the-loop evaluation pipelines with reproducible scoring, statistical significance, and error analysis.</li><li>Establish SLOs/SLIs for quality (e.g., grounded accuracy, hallucination rate, privacy leak rate, harmful-content rate).</li></ul>Red-Teaming &amp; Safety Guardrails<ul><li>Design and run red-teaming against prompt injection, jailbreaks, sensitive data leakage, tool-abuse, and retrieval abuse.</li><li>Develop guardrail solutions (classification, content safety, PII/PHI detection, grounding checks, allow/deny lists, rate limiting, output filtering) to mitigate hallucinations, leakage, and compliance violations.</li><li>Maintain attack libraries and scenario banks; simulate adversarial behavior and monitor adaptive attacks over time.</li></ul>Pre‑Release Gating &amp; Continuous Assurance<ul><li>Operate pre‑release evaluation gates with baselines, regression checks, canary/A–B testing, and rollback criteria.</li><li>Run continuous evaluation in production with synthetic &amp; real traffic (shadow/ghost testing) and drift, bias, and toxicity monitoring.</li></ul>Stakeholder Leadership &amp; Culture<ul><li>Coach product teams on responsible AI practices and establish quality ownership norms.</li><li>Build a community of practice across Engineering, Security, Data Governance, and Risk—standardizing test data, benchmarks, and review rituals.</li><li>Mentor engineers building evaluation, red-team, and guardrail capabilities.</li></ul>BASIC QUALIFICATIONS<ul><li>7+ years in ML/AI/Platform/Quality roles, including 3+ years evaluating production systems.</li><li>Advanced degree in Computer Science, Engineering or related discipline.</li><li>Proven design &amp; operation of evaluation harnesses and policy-as-code checks in CI/CD.</li><li>Hands-on Python and expertise with evaluation and safety tooling such as: OpenAI Evals, Ragas/LangSmith, DeepEval, Azure AI Content Safety / OpenAI Moderation, Presidio, Guardrails.ai, Nemo, MLFlow, Grafana, Kibana, Azure monitor</li><li>Cloud &amp; MLOps: Azure/AWS, CI/CD (GitHub Actions/Azure DevOps, feature stores, vector DBs (Azure AI Search, OpenSearch, Pinecone), testing in pipelines.</li><li>Excellent communication with executives and engineers</li><li>Experience leading an engineering team.</li></ul>PREFERRED QUALIFICATIONS<ul><li>Led an AI safety/quality function or enterprise red-team program.</li><li>Prior work with AI based applications, tool use/orchestration, and enterprise data governance.</li><li>Regulatory literacy (e.g., GDPR, EU AI Act readiness), and experience collaborating with Compliance/Risk, Security, and Legal.</li><li>Strong grasp of red-team techniques (prompt/indirect injection, jailbreaks, training data extraction, membership inference, model poisoning, tool abuse).</li><li>Experience with retrieval grounding checks, memory governance, and multi-tenant safety controls.</li></ul>

Director, AI Quality Engineering Lead 4946565

The Transformation, Infrastructure and Enterprise Solutions (TIES) inspires innovations and powers Pfizer’s growth as the technology engine that makes our enterprise operations possible.The role is responsible for managing and delivering network infrastructure projects (LAN/WLAN, WAN, and Unified Communications/Telephony) across Pfizer Commercial, R&amp;D, and PGS sites in the EMEA region, including full ownership of project planning, scoping, design, costing, execution, and coordination.This role reports and partners with the TIES Real Estate Infrastructure Regional Lead for EMEA on overall planning and will collaborate with the GWE, R&amp;D, and PGS sites, network engineering SMEs and external vendors.This role will work primarily on real estate portfolio including but not limited to new site buildouts, existing site modifications, site closures, site disposition activities, new infrastructure technology rollouts and changes to existing service offerings.This role ensures operational requirements are captured within project plans, changes are completed in a controlled manner, and there is a formal operational acceptance process during project close-out.This position helps drive continuous improvement to our service offerings, standard patterns, and overall project execution process. Additionally brings an innovative mindset to the team with the goal of leveraging AI through all facets of our work processes and project management methodologies.ROLE RESPONSIBILITIESPartner with TIES Real Estate Solutions Management Infrastructure Lead - EMEA to capture project and ongoing costs before work is committed.<ul><li>Leads planning and scheduling of real estate initiatives across Digital Creation Centers, overseeing all phases from design and execution to successful project closeout.</li><li>Identify and escalate cross‑project dependencies, risks, and issues.</li><li>Maintain accurate project plans, portfolio tracker data, and weekly status reporting.</li><li>Lead weekly project meetings to align timelines, deliverables, and actions.</li><li>Provide regional weekly portfolio updates to ensure transparency and alignment.</li><li>Manage ATC processes and ensure smooth transition to operational teams.</li><li>Oversee vendor engagement, including quotes, deliverables, and invoicing.</li><li>Ensure all project costs are reviewed and approved before work begins.</li><li>Initiate and track Purchase Requisitions and Purchase Orders through completion.</li><li>Manage scope, cost, and timeline changes throughout the project lifecycle.</li><li>Ensure complete project documentation and proper closeout.</li><li>Manage end‑to‑end project budgets and update financial trackers.</li><li>Drive continuous process improvement and integration across TIES Service Areas.</li><li>Mentor and support junior team members.</li></ul>BASIC QUALIFICATIONS<ul><li>Degree in Information Technology, Engineering or related technical field, or equivalent experience.</li><li>At least 4-6 years in IT Project Management/Service Lifecycle, including infrastructure transformation projects.</li><li>Network knowledge desired.</li><li>Proven capability leading projects in agile environment; Scrum Master or Product Owner certification preferred.</li><li>Experience in managing medium to large scale and global IT projects.</li><li>Knowledge and experience in: Project Management, managing external service providers, ITIL Service Management Lifecycle framework &amp; processes, and IT Financial Management.</li><li>PMP &amp; ITIL Certifications desired.</li><li>Expertise in Microsoft Office suite and experience with Microsoft Project &amp; SharePoint.</li><li>Excellent oral and written communication skills.</li><li>Diplomatic and customer serviced focused; ability to manage key stakeholders in positive, poised, and effective manner.</li><li>Ability to manage issues very high and very detailed level to facilitate services and infrastructure operations and transitioning.</li><li>Proven experience in effectively communicating technical issues/challenges with non-technical people.</li><li>Solid stakeholder management, negotiation and influencing skills.</li><li>Must be self-motivated, must have an ability to work well in a geographically dispersed, virtual team environment, must exhibit a positive and professional attitude, and a strong team player.</li><li>Provides coaching to junior members of the team.</li></ul>PREFERRED QUALIFICATIONSTechnology Competence &amp; Scale:<ul><li>Good understanding of the specific technology/network engineering areas and a working knowledge across related digital infrastructure components.</li><li>Experience with Jira, including building workflows and automations to streamline processes.</li><li>Experience in creating BI dashboards for data visualization and actionable insights.</li><li>Knowledge of AI‑driven workflows, including tools like Microsoft Copilot, with a strong interest in learning and applying emerging AI technologies.</li></ul>Vendor Management:<ul><li>Demonstrated ability to develop/maintain a deep operational relationship with multiple vendors and holding them accountable for the delivery of various IT service disciplines.</li><li>Ability to partner with vendors to identify solutions / workarounds / alternatives to business needs or to address problems.</li></ul>

Manager, Real Estate Infrastructure - EMEA 4949551

Θέσεις Εργασίας Learning And Development Specialist Νομός Θεσσαλονίκης, Πληροφορική - Σελίδα 4

manager, technical writer 4949154

Pfizer Hellas

director, ai quality engineering lead 4946565

Pfizer Hellas

manager, real estate infrastructure - emea 4949551

Pfizer Hellas

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