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Senior AI Architect

AI LLM Technology Architecture Senior Manager | Senior Level | Full time
Job No. R00286330 | Helsinki
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In the era of Data & AI, the possibilities to make a change are limitless. Join our diverse team of professionals to help our Nordic and global customers envision, design, and land enterprise-grade AI and GenAI architectures that deliver measurable business value. We are looking for Senior AI Architects who can translate strategy into scalable, secure, and cost‑effective designs—spanning classical ML and modern foundation‑model solutions (RAG, agents, copilots)—and guide multidisciplinary teams from discovery to production. In this role, you will work closely with business, security, data, platform, and application teams to integrate AI into core business processes, with strong emphasis on governance, reliability, and compliance (e.g., GDPR).

Your work will span the following areas

  • Enterprise AI architecture & strategy: Define target‑state architectures, reference designs, standards, and decision guardrails for GenAI and ML platforms and solutions
  • Solution patterns for GenAI: Architect RAG pipelines (ingestion, chunking, embeddings, vector search, hybrid retrieval, re‑ranking), agent/tool calling patterns, prompt & context management, and grounding
  • Platform & infrastructure: Design AI platform foundations on public cloud (Azure/AWS/GCP), including landing zones, networking, identity, private endpoints, GPU/accelerator strategy, and cost/performance trade‑offs
  • Data & integration: Integrate AI solutions with lakehouse/data mesh platforms (e.g., Databricks, Spark), document processing pipelines (OCR, parsing), metadata catalogs, and enterprise systems
  • LLMOps/MLOps & SDLC: Establish CI/CD for models, prompts, and chains; evaluation/telemetry, drift detection, canarying/A‑B tests, rollback, and SLOs. Promote engineering best practices
  • Security, privacy & Responsible AI: Lead threat modeling, privacy impact assessments, data minimization, content safety and guardrails, policy enforcement, auditability, and model risk management aligned to GDPR and internal controls
  • Delivery leadership: Run architecture workshops, guide discovery and PoCs, create roadmaps and business cases (TCO/FinOps), and support teams in taking solutions to production at scale
  • Governance & reuse: Contribute to architecture boards, establish reusable blueprints/templates, and mentor engineers and architects

You preferably have experience in some of the following (and interest to grow in the others)

  • Cloud AI platforms: Azure OpenAI & Azure AI/ML, AWS Bedrock & SageMaker, Google Vertex AI; managing managed endpoints and/or self‑hosted models (Llama, Mistral, etc.)
  • Orchestration & agents: Semantic Kernel, LangChain, LlamaIndex; tool/function calling, planner/agent patterns, workflow engines
  • Retrieval & search: Vector databases (Azure AI Search, FAISS, Pinecone, Milvus, Elastic), hybrid search, re‑ranking, embedding model selection
  • Evaluation & quality: Offline/online evaluation, golden datasets, hallucination/groundedness checks, toxicity/safety testing, telemetry & feedback loops
  • Data & pipelines: Lakehouse architectures (e.g., Databricks), Spark, Airflow/Databricks Jobs; eventing/streaming (Kafka/Flink) where relevant to AI workloads
  • Application & integration: API design, event-driven architectures, Python (FastAPI) and/or TypeScript/Node.js; integration with enterprise apps and APIs
  • Platform engineering: Kubernetes/containers, service mesh, API gateways, caching, vector index ops; Infrastructure as Code (Terraform/Bicep) and CI/CD (GitHub Actions/Azure DevOps/GitLab)
  • Security & compliance: IAM/privileged access, secrets management, network isolation, data protection; GDPR/PII, ISO 27001 controls, audit and monitoring
  • Observability: Logging/metrics/tracing , cost monitoring/FinOps, reliability engineering practices

To succeed in this role, we expect the following key qualifications:

  • Degree in Computer Science, Engineering, or a related technical field
  • 7+ years designing and delivering cloud or distributed systems, including 3+ years in applied ML/AI (with hands‑on GenAI solution architecture preferred)
  • Proven ability to lead architecture for complex enterprise solutions—facilitating workshops, driving architectural decisions (ADRs), and aligning cross‑functional stakeholders from security to product owners
  • Demonstrated understanding of end‑to‑end AI solution lifecycle: from discovery and data grounding to evaluation, safety, deployment, and operations
  • Solid software engineering and architecture skills: Git, testing strategies, documentation, CI/CD, agile ways of working
  • Strong communication and consulting skills—able to articulate technical trade‑offs, TCO, and business impact at both executive and engineering levels
  • Good presentation and communication skills

Why Accenture?

  • Because people enjoy working here; the work we do is challenging, interesting and meaningful.
  • Accenture offers a unique career experience and unparalleled opportunity for you to grow and advance. We are driven by the best results, but we never forget to support each other. We like to challenge our employees and give them the opportunity to shine and succeed. We invest heavily in our people’s growth and knowledge development.
  • Our best and only asset is our people. We believe they’re at their best when knowing what is expected from them and we want to support them in different life phases. Our extensive MyWellbeing –program is one of our key tools for that.

Accenture welcomes and encourages applications from diverse backgrounds related to gender, ethnicity, culture, age etc. We provide an environment of inclusion and diversity where everyone brings distinct experience, talent and culture to their work. We invite you to be part of this diversity!

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