• Define AI Platform Strategy • Shape enterprise design and strategy for AI platforms • Establish scalable patterns for model access and orchestration • Design enterprise-grade AI systems • Create reference architectures for AI applications • Drive responsible AI adoption and governance • Lead and mentor engineering teams • Partner with senior leaders across departments to deliver AI platform capabilities

• Ти очолиш розробку та запуск двох AI-систем: • AI-Tutor — персональний тьютор кожного співробітника, інтегрований у Slack / KissMychat • AI-Assistant — інструмент L&D-команди для генерації контенту, управління knowledge base та аналітики • Визначати vision, roadmap та пріоритети розвитку AI Learning Platform. • Формувати backlog, описувати user stories та вимоги до функціоналу. • Працювати з технічною командою та AI-інтеграторами над запуском нових можливостей. • Контролювати якість продукту та забезпечувати його розвиток відповідно до бізнес-цілей. • Проєктувати користувацький досвід взаємодії з платформою. • Будувати learning journeys для різних ролей та команд. • Забезпечувати якість AI-генерованого контенту та процесів його перевірки. • Визначати ключові продуктові метрики та аналізувати їх. • Відстежувати adoption, completion rate, learning score, engagement та інші показники. • Аналізувати поведінку користувачів і знаходити точки росту продукту. • Приймати продуктові рішення на основі даних та фідбеку користувачів. • Розвивати competency framework компанії. • Створювати learning paths для ключових ролей. • Інтегрувати навчання у performance management процеси. • Побудувати Readiness Dashboard для оцінки готовності співробітників до нових ролей та рівнів. • Впливати на ефективність усієї компанії через розвиток внутрішніх продуктів. • Працювати на перетині Product Management, AI, HR Tech та Knowledge Management. • Мати високий рівень автономії, приймати продуктові рішення та впливати на roadmap.

Role Description As a Sr GCP Engineer, you are the resident expert and engineering heart of our AI & Agentic capabilities. You serve as the lead specialist and authority on building and scaling agentic systems specifically within the Google Cloud ecosystem. Your role is to bridge the gap between AI models and production-ready applications by building the scalable backend services, APIs, and data pipelines required for enterprise AI. Responsibilities - AI Service & Agent Engineering: Build and maintain production-grade microservices and APIs that orchestrate Agent workflows using tools like Gemini Enterprise (fka Agentspace), CX Agent Studio, Vertex AI Agent Builder, Generative Playbooks, and the Agent Development Kit (ADK). - Gemini Prompt & Behavior Engineering: Implement and optimize complex prompt templates, system instructions, and few-shot examples for Gemini models; tune agentic behavior through iterative testing and feedback loops. - Productionizing AI Systems: Lead the transition of AI prototypes to scalable production environments using Cloud Run, GKE, Vertex AI Agent Engine, and Cloud Functions, incorporating advanced patterns like Function Calling, Grounding with Google Search, and Vertex AI Extensions. - Data & Tool Integration: Implement the "glue code" and connectors required for Agents to interact with enterprise data via Gemini Enterprise (fka Agentspace), Vertex AI Search and Conversation (fka Gen AI App Builder), BigQuery, and specialized Vector Databases. - Engineering Standards & CI/CD: Establish automated deployment pipelines (Cloud Build) and MLOps-aligned engineering practices specifically for LLM applications (e.g., prompt versioning, evaluation pipelines). - Innovation Lab Asset Development: Serve as the lead engineer for the GCP Innovation Lab, responsible for the hands-on development of strategic accelerators, POCs, and high-fidelity demos; translate innovative IP and project-based learnings into reusable technical assets and "starters" that optimize delivery speed. - Cross-Practice Collaboration: Partner with AI specialists and lead developers from other technology practices to exchange cross-platform insights and ensure global best practices are translated effectively into optimized GCP implementations. - Asset Creation: Develop reusable "AI Starter Kits" and backend templates that allow our delivery teams to rapidly stand up secure, Gemini-powered applications on GCP. Qualifications - 8+ years of software engineering with a focus on backend development. - 3+ years of experience building applications on Google Cloud Platform. - Expert proficiency in Python and/or Go. - Deep hands-on experience with Gemini (Pro/Flash), Vertex AI SDKs, Prompt Engineering, and Function Calling. - Familiarity with building RAG-based systems. Requirements - Google Professional Cloud Developer certification. - Practical knowledge of the Agent Development Kit (ADK) and Vertex AI Agent Builder. - Experience with Terraform for infrastructure-as-code. - Knowledge of LLM evaluation frameworks. - Hands-on experience with other industry-leading models (e.g., GPT-4, Claude, Llama) for cross-model prompt engineering, supervised fine-tuning (SFT), and the implementation of AI safety guardrails and observability. - The majority of work is performed remotely, so travel is expected to be fairly low (<15%) - largely driven by conferences, client sales meetings, and an occasional client delivery meeting (ex: project kickoff). Company Description We're Concentrix. The intelligent transformation partner. Solution-focused. Tech-powered. Intelligence-fueled. The global technology and services leader that powers the world’s best brands, today and into the future. We shape new game-changing careers in over 70 countries, attracting the best talent. The Concentrix Technical Products and Services team is the driving force behind Concentrix’s transformation, data, and technology services. We integrate world-class digital engineering, creativity, and a deep understanding of human behavior to find and unlock value through tech-powered and intelligence-fueled experiences. Our game-changers around the world have devoted their careers to ensuring every relationship is exceptional. And we’re proud to be recognized with awards such as "World's Best Workplaces," “Best Companies for Career Growth,” and “Best Company Culture,” year after year.

• Set technical direction: Own architecture for our most complex GenAI and agentic systems end-to-end, and set the standards — evaluation, observability, responsible AI — that the practice builds to. • Build at the frontier, hands-on: Stay in the code where it matters most — foundation-model and embedding fine-tuning, novel agentic workflows, advanced RAG and semantic search — using Python on Google Cloud (Vertex AI), LangChain/LlamaIndex, and vector search (Vertex AI Vector Search, Pinecone, pgvector). • Engineer for production: Design for latency, reliability, cost, and scale from day one; apply MLOps discipline so systems are served efficiently, monitored, and continuously improved — and actually reach production, where most AI work stalls. • Lead multi-step reasoning at scale: Architect and operate agentic workflows that automate complex reasoning reliably, with the design and verification discipline that keeps multi-agent systems from cascading into failure. • Advise clients and shape deals: Work directly with client leadership to understand strategy, propose state-of-the-art approaches, and shape solutions in pre-sales — the technical authority in the room. • Multiply the team: Elevate senior and mid-level engineers through architecture reviews, mentorship, and setting a high, teachable bar for AI-augmented engineering.