AI Automation Architect

227k - 421.4k PLN227 000 - 421 400 PLN/ rok./ rok.

SeniorOn-site·WarszawaFull-time

#473268·Dodano wczoraj·0

Źródło: IQVIA

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Tech Stack / Keywords

PythonRAGOpenAIAzure OpenAIAnthropic ClaudeLangChain LangGraph FastAPI Kubernetes Docker

Podsumowanie oferty

Design and scale enterprise-grade Agentic AI, Copilot, and intelligent automation solutions. The role covers AI architecture, enterprise data strategy, evaluation engineering, governance, and process automation, with Python-based AI platforms and integrations across business systems.

Wymagania

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
8+ years of software engineering experience, including at least 3 years focused on AI/ML, Generative AI, Agentic AI, Copilot, or intelligent automation solutions.
Strong expertise in Python, including development of AI agents, APIs, automation services, data processing pipelines, orchestration frameworks, and evaluation platforms.
Hands-on experience building enterprise AI applications with technologies such as FastAPI, LangChain, LangGraph, and Pandas, or similar frameworks.
Hands-on experience with Cursor AI, GitHub Copilot, and Microsoft 365 Copilot.
Extensive experience with LLM platforms including OpenAI, Azure OpenAI, and Anthropic Claude, or similar technologies.
Deep understanding of RAG, vector databases, embedding models, enterprise search, knowledge management architectures, and AI evaluation frameworks.
Strong knowledge of Graph APIs, OAuth2, SSO, enterprise integration patterns, API design, microservices, Docker, Kubernetes, event-driven architecture, and CI/CD pipelines.
Experience designing AI evaluation datasets, benchmark frameworks, quality gates, model performance metrics, and validation methodologies.
Experience building AI business cases, value realization frameworks, ROI assessments, and executive-level presentations.

Preferred Qualifications:

Experience leading enterprise-scale Agentic AI and multi-agent deployments.
Knowledge of model fine-tuning, reinforcement learning, and model optimization techniques.
Familiarity with Model Context Protocol, AI orchestration platforms, and agent communication protocols.
Exposure to MLOps, LLMOps, prompt management, model monitoring, and AI compliance frameworks.

Obowiązki

Architecture & Solution Design:

Design and deliver enterprise-grade Agentic AI, Copilot, RAG, and intelligent automation solutions.
Architect multi-agent systems covering planning, reasoning, memory management, workflow orchestration, tool integration, and Human-in-the-Loop controls.
Define enterprise AI strategy, reference architectures, standards, governance frameworks, best practices, and reusable accelerators.
Lead platform decisions across foundation models, agent frameworks, enterprise data, orchestration platforms, and integration patterns.
Provide technical leadership for Python-based AI platforms, agent frameworks, automation services, APIs, and enterprise integrations.
Ensure solutions meet enterprise requirements for scalability, reliability, observability, security, compliance, and operational excellence.
Collaborate with product, engineering, security, data, and business stakeholders to identify AI opportunities and deliver measurable business impact.
Conduct architecture reviews, support Architecture Review Boards, and oversee delivery across multiple AI initiatives.

Enterprise Integration, Data & AI Quality Engineering:

Integrate AI solutions with ERP, CRM, ITSM, HR, Finance, SharePoint, and other business systems.
Design AI architectures using Microsoft Fabric, Databricks, Snowflake, Azure Data Lake, enterprise data platforms, and knowledge repositories.
Architect secure integrations using APIs, Graph APIs, OAuth2, Function Calling, MCP, agent-to-agent communication, and event-driven architectures.
Design enterprise knowledge architectures across structured, semi-structured, and unstructured data sources.
Define data strategies for knowledge sourcing, metadata management, chunking, embeddings, vectorization, and retrieval optimization.
Design scalable data processing pipelines, orchestration services, and AI workloads using Python and cloud-native technologies.
Design evaluation datasets, benchmark suites, golden test sets, and domain-specific validation frameworks.
Establish methods to measure accuracy, groundedness, relevance, reasoning quality, latency, cost efficiency, and business outcomes.
Define evaluation pipelines for prompts, RAG systems, copilots, and autonomous agents using automated and human evaluation.
Partner with business, domain, and data teams to establish AI-ready data foundations, feedback loops, and continuous improvement processes.

Governance, Security & Reliability:

Implement Responsible AI practices covering privacy, security, compliance, auditability, risk management, ethical AI, and PII protection.
Define observability, testing, hallucination detection, resiliency, disaster recovery, model monitoring, and operational support strategies.
Establish AI quality gates, release criteria, evaluation standards, and governance processes for production AI systems.
Drive token governance, model routing, semantic caching, cost optimization, and mitigation strategies for bias, drift, and reliability risks.

Foundation Models & GenAI:

Provide technical leadership on LLM platforms including OpenAI GPT, Azure OpenAI, Anthropic Claude, Microsoft Copilot, and emerging foundation models.
Apply prompt engineering, context engineering, knowledge grounding, Function Calling, agent memory, and model routing techniques.
Design and optimize Retrieval-Augmented Generation solutions using enterprise search, vector databases, embeddings, and knowledge management platforms.

Benefity

Depending on the position offered, incentive plans and/or bonuses may be offered.

Premie

IQVIA

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