PwC jobs

Join our technology consulting team as a Medior AI Engineer, specializing in generative AI development. You will work on innovative projects, applying large language models (LLMs) and generative AI in sectors like finance and energy, and accelerating internal workflows. This role offers the chance to learn from leading experts, fundamentally change business operations with technology, and gain exposure to diverse industries. You will be part of a dynamic GenAI Lab, with opportunities for rapid growth and competitive compensation in a challenging and dynamic work environment. You will engage with various business units and internal decision-makers to identify and implement new use cases, taking ownership of Proof of Concept (PoC) projects from planning to delivery, working closely with senior experts to ensure high-quality results and continuous professional development.

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The opportunity is to build, test, and integrate production-grade AI agents and services that reliably execute business tasks within enterprise workflows. This role involves implementing agents, prompts, tools, retrieval pipelines, and orchestration logic, as well as integrating AI components with enterprise APIs, applications, databases, and workflow services. You will also build automated tests and evaluation datasets, diagnose failures in models, retrieval, and tool usage, and contribute to secure coding, documentation, peer reviews, and release activities.

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We are seeking a Lead AI Engineer to provide hands-on engineering leadership for agentic AI products. You will define implementation patterns, ensure technical quality from prototype through production, and lead the technical design and implementation of agents, RAG services, tool integrations, and model orchestration. This role involves establishing coding, testing, evaluation, review, and documentation standards, decomposing architecture into engineering work, guiding estimation and sprint planning, coaching engineers, reviewing code, and resolving complex technical problems. You will also design evaluation suites for quality, safety, reliability, latency, and cost, and work with architects and MLOps to harden solutions for production.

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The opportunity involves designing and implementing end-to-end, client-specific AI architectures. This role focuses on integrating agents, models, enterprise data, applications, identity, and controls across both cloud and on-premises environments. You will translate business requirements into actionable architecture and implementation decisions, design various AI patterns including agentic workflows, RAG, and human-in-the-loop systems, and define hybrid deployment strategies considering constraints like residency, latency, security, performance, and cost. The role also includes evaluating technology choices, documenting architectural decisions and trade-offs, providing technical assurance during delivery, and collaborating with governance, Responsible AI, cyber, and privacy specialists.

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We are seeking a Senior Operations AI Engineer to join our Procurement and Supply Chain team in Athens. This is a senior-level, hands-on technical leadership role for a passionate technologist with deep expertise in Machine Learning, Artificial Intelligence, and modern software engineering. You will architect AI systems that make operational decisions, sitting at the intersection of AI engineering and operational excellence. Your work will involve designing and delivering intelligent systems that autonomously monitor, reason, and optimize large-scale supply chain, logistics, and operations environments, acting as the go-to technical authority for your team and clients.

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We are seeking an AI Platform Architect to design and evolve the reusable platform capabilities necessary for building, deploying, securing, observing, and scaling AI products across hybrid environments. This role involves defining reference platforms, environment topologies, network patterns, and access controls. You will design model access, compute, storage, vector services, orchestration, gateways, and shared platform services, supporting various deployment choices including cloud, sovereign, edge, and on-premises. A key aspect of this role is defining platform non-functional requirements for availability, performance, resilience, scalability, and cost, while creating reusable landing patterns and platform guardrails for delivery squads. You will also partner with MLOps Engineers on environment automation, observability, and release management.

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