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As Senior Manager, Evaluation &amp; QA Engineer (Individual Contributor), you will own the quality, evaluation, and reliability strategy for our pip‑installable AI Capabilities SDK and its reusable modules (RAG components, agent/tool cookiecutters, MCP adaptors, standardized interfaces). You will design evaluation frameworks, test harnesses, and automation pipelines that make quality measurable and repeatable—from unit and integration tests to adversarial/fuzz testing, performance/cost benchmarking, and safety/privacy checks.You will collaborate closely with:<ul><li>Embedded AI Architects and Solution Designers to codify evaluation requirements that mirror real solution patterns.</li><li>AI Engineering to validate PI increments, integrate external technologies, and capture model/agent‑level failure modes.</li><li>DevOps Engineers to wire evaluation gates into CI/CD and release trains.</li><li>Developer Experience Engineers to ensure developers receive clear, actionable evaluation reports and quickstarts.</li><li>Digital Creation Centers and Forward Impact Teams (FITs) to gather field feedback and ensure tests reflect production reality.</li></ul>&nbsp;Why this Role MattersFor modular AI capabilities to scale safely and predictably, we need evidence‑driven quality. This role turns evaluation into a first‑class, automated discipline—ensuring every SDK change is validated for correctness, performance, safety, and operability. You will reduce regressions, raise confidence, and accelerate adoption across products and services that rely on the SDK as their backbone.ROLE RESPONSIBILITIES1) Evaluation Strategy &amp; Quality Architecture<ul><li>Define the evaluation strategy for SDK modules (parsers, retrievers, rankers, connectors, agent tools, MCP adaptors), including metrics, datasets/fixtures, benchmarks, and acceptance thresholds.</li><li>Establish quality gates for release: test coverage minimums, latency/throughput/cost budgets, stability envelopes, and backward compatibility checks.</li><li>Establish source code writing principles that align with the widely accepted coding standards and ensure high maintainability degree.</li><li>Create reproducibility standards (seeds, dataset/version pins, environment parity) and evidence capture (reports, artifacts) for auditability.</li></ul>2) Test Harnesses &amp; Automation<ul><li>Build unit, integration, contract, property‑based, and fuzz/adversarial test harnesses for SDK components; standardize fixtures for RAG and agent scenarios (vector stores, document corpora, tool execution).</li><li>Partner with DevOps to integrate tests and quality gates into CI/CD (parallelization, matrix runs, caching) and to fail builds on significant regressions or unmet quality bars.</li><li>Design benchmark suites for performance and cost profiling (e.g., latency distributions, throughput, memory/CPU footprints) with clear pass/fail criteria.</li></ul>3) Safety, Privacy &amp; Guardrails<ul><li>Codify safety evaluations (toxicity/abuse prompts, jailbreak resistance, sensitive data leakage risks) and policy adherence tests for agent/tool behaviors.</li><li>Validate security-by-design aspects of SDK usage (authn/z integration points, secrets handling, data minimization); coordinate with Platform/Security for service consumers.</li><li>Ensure privacy and compliance checks are represented in test plans and evidence bundles (PII handling, retention, deletion workflows).</li></ul>4) Observability-by-Design for Libraries<ul><li>Work with Capability Architecture and DevOps to embed diagnostic hooks suitable for libraries (structured logging, metrics/traces toggles) and define SLIs relevant to consuming services.</li><li>Verify error models (exceptions/types/codes) and retry/backoff behaviors; ensure runbooks and troubleshooting guides are informed by evaluation results.</li></ul>5) Data &amp; Datasets Governance for Evaluation<ul><li>Curate and version evaluation datasets (synthetic and real-world samples where appropriate); maintain data lineage and provenance.</li><li>Implement dataset health checks (drift, representativeness, coverage) and red‑team suites that evolve with product use cases.</li><li>Align dataset usage with legal/privacy guidance; document constraints and approvals.</li></ul>6) Developer Experience &amp; Enablement<ul><li>Produce evaluation reports and quality dashboards that developers can interpret quickly (summary + drill‑downs + diffs vs. baseline).</li><li>Collaborate with Technical Writers and Developer Experience engineers to include evaluation guidance, quickstarts, and troubleshooting in SDK docs.</li><li>Provide templates for teams to extend evaluation suites when contributing new modules via feature branches.</li></ul>7) Collaboration &amp; Continuous Improvement<ul><li>Close feedback loops with Embedded Architecture, Solution Design, AI Engineering, Creation Centers, and FITs to keep evaluation aligned with production realities.</li><li>Lead post‑release and incident reviews to improve test coverage, resilience, and guardrails.</li><li>Track and improve quality KPIs (escaped defects, regression counts, benchmark variance, time-to-detect/repair).</li></ul>MEASURES OF SUCCESS<ul><li>Safety &amp; compliance: Guardrail tests pass; reduced policy violations; documented evidence meets audit requirements.</li><li>DX &amp; adoption: Clear evaluation reports improve developer confidence; faster time‑to‑first‑success for consuming teams.</li><li>Continuous Improvement: Actionable insights from incidents and field feedback lead to expanded test suites and stronger guardrails.</li><li>Process Excellence: Data-driven evaluation of the efficiency, quality and consistency of the SDK testing and quality workflows.</li></ul>QUALIFICATIONSBasic Qualifications<ul><li>7+ years in QA/Quality Engineering/Evaluation for SDKs, libraries, or platform components in software/AI contexts.</li><li>Hands‑on experience building automated test frameworks (unit/integration/contract) and benchmark suites; strong Python testing fluency (e.g., pytest, property-based testing, fuzzing).</li><li>Proficiency with CI/CD systems (GitHub Actions, Azure DevOps, GitLab CI) and integrating quality gates (coverage, performance, security).</li><li>Working knowledge of AI/ML or GenAI patterns (RAG, vector stores, agents/tools) and evaluation considerations for these workloads.</li><li>Strong grasp of reproducibility, data governance, and observability‑by‑design for libraries.</li></ul>Preferred Qualifications<ul><li>Experience with adversarial/red‑teaming methodologies for LLM‑enabled features and safety guardrails.</li><li>Background in performance engineering (profiling, optimization, latency/cost analysis) for Python libraries.</li><li>Familiarity with security and privacy testing (static analysis, secrets scanning, dependency hygiene, PII handling).</li><li>Exposure to regulated environments (healthcare/pharma/finance) and audit‑ready evidence capture.</li><li>Comfortable collaborating across architecture, DevOps, DX, LLMOps, platform, and product teams in matrixed organizations.</li></ul>

Senior Manager, Evaluation & QA Engineer 4949162

As Senior Manager, LLMOps &amp; AI Integration Engineer (Individual Contributor), you will lead the model integration, agent/tooling, and LLM operations strategy for our pip‑installable AI Capabilities SDK. You will design and maintain clean, extensible interfaces for LLMs, embeddings, retrieval, tool execution, and agentic workflows; build runtime guards and evaluation hooks; and optimize latency, reliability, and cost—so teams can embed AI safely and predictably.You will collaborate closely with:<ul><li>Embedded AI Architecture and Solution Design to prioritize capabilities and define interfaces aligned to real-world solution patterns.</li><li>AI Engineering to deliver PI increments, integrate external technologies, and codify model/agent failure modes and mitigations.</li><li>Digital Creation Centers and Forward Impact Teams (FITs) as consumers of the SDK, capturing feedback to refine ergonomics and performance.</li><li>DevOps, Evaluation &amp; QA, and Developer Experience engineers to wire guardrails, evaluation, and developer-ready assets into CI/CD and docs.</li></ul>Why this Role MattersLLMOps sits at the intersection of capability, safety, and operability. By turning complex model/agent behaviors into well-abstracted, evaluable, and observable SDK modules, you enable teams to deliver AI features fast with safety—reducing bespoke implementations, ensuring reproducibility, and controlling latency/cost at scale. Your work is foundational for platform services that rely on the SDK as their backbone.ROLE RESPONSIBILITIES1) Model &amp; Agent Integration Architecture<ul><li>Design Python SDK interfaces for LLM clients, embeddings, tokenization, and structured outputs (e.g., Pydantic/JSON schemas).</li><li>Implement function/tool calling abstractions, agent orchestration patterns (ReAct-like, planner/executor), and MCP adaptors for interoperable tools.</li><li>Provide configuration and secrets integration points that downstream services can adopt consistently (env vars, config schemas, key management hooks).</li></ul>2) Retrieval &amp; RAG Components<ul><li>Build RAG modules (document loaders, chunking/segmentation, embeddings, retrievers, rerankers) with pluggable backends (vector stores, search indices).</li><li>Standardize connectors and interface contracts for common data sources; ensure reproducible pipelines and SDK↔service parity of behaviors.</li><li>Optimize retrieval quality via evaluation hooks (precision/recall, MRR, hit rate) and tunable parameters (top‑k, thresholds).</li></ul>3) Guardrails, Safety &amp; Policy Integration<ul><li>Codify safety guardrails: prompt hygiene, jailbreak resistance, content filters, sensitive topic/policy checks, red‑team/adversarial probes.</li><li>Integrate privacy/security controls: data minimization, PII detection flags, safe logging, and deterministic truncation strategies.</li><li>Provide policy‑as‑code hooks and pre/post‑processing middleware to enforce runtime constraints within SDK flows.</li></ul>4) Performance, Reliability &amp; Cost Engineering<ul><li>Implement caching, batching, retry/backoff, circuit breakers, and fall‑back strategies across model/tool calls.</li><li>Profile and tune latency, throughput, and token usage/cost; expose configuration knobs and budget guards (token and cost caps).</li><li>Maintain benchmark suites and regression baselines for model and retrieval components; block releases on significant degradations.</li></ul>5) Observability‑by‑Design for Libraries<ul><li>Embed telemetry hooks (structured logs, metrics, traces) suitable for a library so that services consuming the SDK can attach enterprise observability.</li><li>Define SLIs relevant to LLMOps (latency, error rates, cache hit ratio, token usage, cost per call) and document runbook guidance for downstream teams.</li><li>Standardize error models and return types to ensure predictable handling across consuming services.</li></ul>6) Evaluation &amp; CI/CD Integration<ul><li>Partner with Evaluation &amp; QA Engineers to build test harnesses (unit/integration/contract/fuzz/adversarial) and benchmark suites for agents/tools, RAG, and model endpoints.</li><li>Work with DevOps Engineers to wire quality gates into CI/CD: coverage thresholds, performance budgets, safety checks, SBOM/signing for release artifacts.</li><li>Provide fixtures and simulators to enable deterministic tests across backends (vector stores, providers).</li></ul>7) Developer Experience &amp; Enablement<ul><li>Collaborate with Developer Experience and Technical Writers to deliver quickstarts, sample apps, notebooks, and code recipes for common patterns (RAG, agents, tool use, structured outputs).</li><li>Contribute to cookiecutters/CLI scaffolds that prewire configuration, tests, telemetry, and guardrails for new modules or integrations.</li><li>Support community contribution workflows (feature branches, PR checks, doc acceptance criteria) and mentor contributors on best practices.</li></ul>8) Collaboration &amp; Continuous Improvement<ul><li>Close feedback loops with Embedded Architecture, Solution Design, AI Engineering, Creation Centers, and FITs to refine APIs, defaults, and ergonomics.</li><li>Participate in post‑release retrospectives and incident reviews to strengthen guardrails, performance tuning, and developer experience.</li><li>Track and improve LLMOps KPIs (latency, cost per call, error rates, cache hit ratios, evaluation pass rates).</li></ul>MEASURES OF SUCCESS<ul><li>Performance &amp; cost: Latency and token/cost budgets consistently met; cache hit ratios improved; fewer performance regressions.</li><li>Safety &amp; reliability: Guardrail tests pass; reduced policy violations and incident rates; predictable error handling.</li><li>Adoption &amp; DX: Faster time‑to‑first‑success for consuming teams; positive developer feedback on APIs and examples.</li><li>Evaluation coverage: Benchmarks and adversarial tests integrated; high pass rates; clear baselines with trend reporting.</li><li>SDK↔Consumer parity: Consistent behavior across downstream services; reduced bespoke integrations and rework.</li></ul>QUALIFICATIONSBasic Qualifications<ul><li>7+ years in software/AI engineering with significant experience in LLMOps or model/tool integration for Python libraries.</li><li>Deep proficiency in Python and building extensible SDKs (interfaces, packaging, semantic versioning, backward compatibility).</li><li>Hands‑on with GenAI/LLM ecosystems (e.g., tool/function calling, structured outputs, prompt orchestration) and RAG components (embeddings, retrievers, rerankers, vector stores).</li><li>Strong grasp of performance engineering (profiling, caching, batching), resilience patterns (retry/backoff, circuit breakers), and cost control (token budgeting).</li><li>Experience embedding observability hooks and integrating evaluation/benchmarks into CI/CD pipelines.</li></ul>Preferred Qualifications<ul><li>Familiarity with agent frameworks, MCP adaptors, and multi‑provider model client abstractions.</li><li>Experience with adversarial/safety testing, privacy/PII considerations, and policy‑as‑code guardrails.</li><li>Background in open-source workflows (feature branches, PR reviews) and multi‑backend integration (vector DBs, search, storage).</li><li>Exposure to regulated environments (healthcare/pharma/finance) and audit‑ready evidence capture.</li><li>Comfortable collaborating across architecture, DevOps, QA, DX, platform, and product teams in matrixed organizations.</li></ul>

Senior Manager, LLMOps & AI Integration Engineer 4949157

What Impact will you make? GenAI Engineer @ Deloitte Alexander Competence Center Are you looking for an&nbsp;opportunity&nbsp;in&nbsp;Thessaloniki, that offers you a&nbsp;hybrid working model? Are you ready to work on&nbsp;international projects for industry-leading clients&nbsp;around the world and elevate your&nbsp;tech consulting career&nbsp;to an&nbsp;international level? If so, check below for more info about this career opportunity! You bring passion, we bring opportunities! #YourOpportunity Deloitte is a worldwide leader in Professional Services with a presence in more than 150 countries and territories.&nbsp;Since 2018, Deloitte has been operating its Alexander&nbsp;Competence Center in Thessaloniki with satellites in the cities of Patras, Heraklion, and Ioannina&nbsp;- which are model hubs of expertise, training, and innovation, specializing in cutting-edge exponential technologies, in which graduates and young professionals undergo immersive experiences, continuous learning, gaining practical insights and hands-on training that empower them to navigate the complexities of the digital landscape. Deloitte is an ideal working environment for&nbsp;both young and senior professionals&nbsp;who want to take the next step in their careers, offering them a supportive and international working environment that leverages their expertise and potential. Its corporate culture is based on trust and collaboration and ensures diversity and inclusion so that everyone feels part of a great team.#YourServiceLine:&nbsp;Technology &amp; Transformation​Our Technology &amp; Transformation teams empower organizations to navigate the future through technology-driven business transformation. Combining deep industry knowledge with cutting-edge technology, we deliver tailored solutions that drive innovation, enhance efficiency, promote cybersecurity, and foster sustainable growth.​#AboutYourRole We are seeking talented&nbsp;AI Engineers&nbsp;to join our team in Thessaloniki. In this role, you will design and build AI-driven applications using&nbsp;Python&nbsp;and other modern programming languages, with a strong focus on&nbsp;Generative AI technologies. You will work on integrating&nbsp;Large Language Models (LLMs)&nbsp;into real-world solutions. This involves using modern frameworks to develop scalable backend services, integrating vector databases and retrieval techniques, and deploying them in production environments.#YourRoleandResponsibilities <ul><li>Design and implement efficient, scalable, and maintainable code using&nbsp;Python&nbsp;and other modern programming languages.</li><li>Develop robust AI-driven applications using frameworks such as&nbsp;FastAPI, Flask, or Django.</li><li>Collaborate closely with AI specialists to integrate&nbsp;LLMs and GenAI tools&nbsp;into applications.</li><li>Integrate&nbsp;embedding models,&nbsp;vector databases, and&nbsp;RAG pipelines&nbsp;to enhance knowledge retrieval and context.</li><li>Manage containerization and deployment processes using&nbsp;Docker&nbsp;and&nbsp;DevOps&nbsp;best practices.</li><li>Ensure high levels of application performance, usability, and reliability.</li><li>Work with cross-functional teams (AI/ML, product, design) to define and deliver new features.</li><li>Stay up to date with emerging&nbsp;AI tools, frameworks, and trends, especially in the GenAI/ AI space.</li><li>Participate in code reviews, contribute to documentation, and ensure adherence to best practices.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</li></ul>#OurRequirements&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<ul><li>Bachelor’s degree in Computer Science, Electrical &amp; Computer Engineering, or a related field (open to recent graduates).</li><li>Strong programming skills in&nbsp;Python&nbsp;(preferred) or another modern programming language.</li><li>Familiarity with integrating&nbsp;LLMs&nbsp;into applications using tools such as&nbsp;LangChain,&nbsp;LlamaIndex, or similar.</li><li>Understanding of&nbsp;prompt engineering,&nbsp;embedding models, and&nbsp;vector databases&nbsp;(e.g., FAISS, Pinecone, Chroma).</li><li>Hands-on experience using&nbsp;LLM APIs&nbsp;(e.g., OpenAI, Anthropic, Cohere) and pre-trained models for real-world solutions.</li><li>Previous exposure to&nbsp;Retrieval-Augmented Generation (RAG)&nbsp;or similar context-enhancement techniques is a plus.</li><li>Experience with&nbsp;web frameworks&nbsp;such as FastAPI, Django, or Flask for building backend services and RESTful APIs.</li><li>Version control skills using&nbsp;Git&nbsp;and a good understanding of RESTful service design.</li><li>Production-oriented mindset with an eagerness to build reliable, scalable, and maintainable solutions.</li><li>Demonstrated passion for learning and experimenting with&nbsp;new AI and GenAI technologies.</li><li>Strong programming skills in at least one modern language, preferably Python.</li><li></li><li></li><li></li><li></li><li>Experience with web frameworks such as FastAPI, Django, or Flask for building backend services and RESTful APIs.</li><li>Experience in using version control tools like Git and a good understanding of server-side logic and REST API design.</li><li>Ability to work collaboratively in a team environment and a production mindset focused on building reliable and maintainable solutions.</li><li></li></ul>#Preferredskills<ul><li>Exposure to cloud platforms (AWS, Azure, GCP) and AI model deployment strategies.</li><li></li><li>Experience developing full-stack applications using front-end technologies (JavaScript, HTML5, CSS) and libraries like React.js.</li><li>Familiarity with backend JavaScript frameworks such as Node.js.</li><li>Familiarity with Docker and basic DevOps practices for containerization and deployment.</li><li></li></ul>#WhoWeAreLookingFor Individuals who have a&nbsp;strong will&nbsp;to expand their knowledge of new technologies, a&nbsp;passion&nbsp;to grow within the company and&nbsp;aspirations&nbsp;for career growth. At Deloitte we foster a consultative culture because the best decisions are made in collaboration with others. We approach our work with a collaborative mindset, teaming across businesses, geographies, and skill sets to deliver tangible, measurable, attributable impact. These are not aspirations, but principles that we all commit to today and every day. #WhatWeOffer At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits:🏠&nbsp;Modern hybrid workplace, characterized by flexibility and Smart Working⚖&nbsp;Empowered well-being: We provide multiple program offerings to support your well-being needs (flexible working arrangements, extra days of leave, parental allowances)🌍&nbsp;Engagement within international large-scale teams and projects, with opportunities to travel for training or client purposes📚&nbsp;Constant opportunities for learning with unlimited access to internal and external learning platforms and sponsored certificates aligned with business needs and technology trends🚀&nbsp;Challenging and innovating environment where personal development and growth are encouraged, always with transparency and trust👬&nbsp;Diverse culture and active communities that enable you to bring yourself to work🎉&nbsp;Team Building and Corporate Social Responsibility Activities🏃&nbsp;A buddy to support you with your onboarding⚕️&nbsp;Private medical health insurance plan💳&nbsp;Ticket restaurant card&nbsp;🛍️&nbsp;Exclusive Discounts to several retail providers, restaurants and others&nbsp;📱&nbsp;Mobile phone&nbsp;🍏&nbsp;Fresh fruits and unlimited coffee everyday at our offices We exist to solve complex problems &nbsp; Our consultants are renowned for their straightforward approach to solving some of the world’s largest and most complex business challenges. Each member of our&nbsp;&nbsp;team is energized by the challenge a seemingly inscrutable problem presents. Our distinctiveness lies in our refusal to accept a problem at face value - we draw on the depth of our shared insight to ask the right questions, and it’s these questions that uncover answers - answers with impact. &nbsp; We are committed to collaboration &nbsp; Our role is to unlock potential for growth and innovation. We believe this requires real collaboration – with our own networks and with our clients. It is why we commit to truly getting under the skin of our client’s needs, developing a full appreciation for their environment, goals and ambitions. We are also unafraid to challenge. &nbsp;In so doing, we build long-term and trusted affinities. &nbsp; We create long-term, sustainable impact &nbsp; We often work hand-in-hand with our clients to help find the right solution and to help apply that solution. Our aim is to leave behind ambassadors who are equipped to continue the transformation we began. For us, it is about embedding sustainable change, allowing the impact of our insight to be felt for a long time to come.&nbsp; #AboutDeloitte &nbsp; Our services &nbsp; Deloitte offers Global professional services that include Audit, Risk Advisory, Tax, Consulting and Financial Advisory. Our approach combines insight and innovation from multiple disciplines with global business and industry expertise to help our clients excel anywhere in the world. &nbsp; We deliver outstanding impact on the reputation and success of our clients, in Greece and globally. In pursuing this we contribute to a sustainable and prosperous society, and are firm believers in the positive impact business can and should have on the world it operates within. &nbsp; Our Purpose &nbsp; Our purpose, “To make an impact that matters for our clients, our people and society “- defines who we are and what we stand for. This is not about size it is about being the first choice. The first choice for the largest and most influential clients and the first choice for the best talent. &nbsp; Our values &nbsp; At Deloitte, we foster a collaborative culture where talented individuals can produce their best work. We value innovative thinking, diverse insights and a genuinely distinctive level of customer service through our expertise and professionalism. &nbsp; We value difference, with respect at the heart of our inclusive culture. &nbsp; Our talent experience &nbsp; From day one at our firm, practitioners are part of a community. Our development and career progression framework will help them develop the skills and capabilities to succeed. The wellness of our people and the ability to offer agile working arrangements is at the center of our unique talent experience. We create a workplace that encourages collaboration, creativity, inclusiveness to ensure our staff are supported, encouraged and feel a sense of purpose and meaning in what they do each day.&nbsp;Sounds like the sort of role for you? Apply now.Location:&nbsp;Thessaloniki This document has been prepared by Deloitte Alexander Competence Center Single Member&nbsp;Societe&nbsp;Anonyme of Business Consultants.&nbsp; &nbsp; Deloitte Alexander Competence Center Single Member&nbsp;Societe&nbsp;Anonyme of Business Consultants, a Greek company, registered in Greece with registered number 144724504000 and its registered office at Thessaloniki, Municipality of&nbsp;Pylaia&nbsp;-&nbsp;Chortiatis&nbsp;of Thessaloniki,&nbsp;Vepe&nbsp;Technopolis Thessaloniki (5th and 3rd street), is one of the Deloitte Central Mediterranean&nbsp;S.r.l.&nbsp;(“DCM”) Countries. DCM, a company limited by guarantee registered in Italy with registered number 09599600963 and its registered office at Via&nbsp;Tortona&nbsp;no. 25, 20144, Milan, Italy is one of the Deloitte NSE LLP Geographies. Deloitte NSE LLP is a UK limited liability partnership and member firm of Deloitte&nbsp;Touche&nbsp;Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”).&nbsp; DTTL and each of its member firms are legally separate and independent entities. DTTL, Deloitte NSE LLP and&nbsp;Deloitte Central Mediterranean&nbsp;S.r.l.&nbsp;do not provide services to clients. Please see&nbsp;<a target="_blank" rel="noopener noreferrer nofollow" href="https://www.deloitte.com/about">www.deloitte.com/about</a>&nbsp;to learn more about our global network of member firms.&nbsp; This document and its contents are confidential and prepared solely for your use, and may not be reproduced,&nbsp;redistributed&nbsp;or passed on to any other person in whole or in part, unless otherwise expressly agreed with you. No other party is entitled to rely on this document for any purpose whatsoever and we accept no liability to any other&nbsp;party, who&nbsp;is provided with or obtains&nbsp;access&nbsp;or relies to this document.&nbsp;© 2025 Deloitte Central Mediterranean. All rights reserved.&nbsp;

Θέσεις Εργασίας Financial Analyst Μακεδονία, Πληροφορική - Σελίδα 2

senior manager, evaluation & qa engineer 4949162

Pfizer Hellas

senior manager, llmops & ai integration engineer 4949157

Pfizer Hellas

genai engineer @thessaloniki

Deloitte

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