Managed AI Lead Consultant

MAKE YOUR STORY REAL

At Siili, we don't just build AI – we run it. We've seen firsthand that capabilities needed to run a compelling proof of concept are fundamentally different from those required to operate AI reliably at scale. That's why we're building our Managed AI practice: to bridge the gap between "it works in the PoC" and "it works in our business."

As a Managed AI Lead Consultant, you will play a key role in helping clients take their AI solutions from pilot to production and keep them running reliably at scale. You'll work as part of our Managed Services business line, alongside developers, data, automation and cloud experts. Your focus will be on operational excellence: ensuring AI systems are deployed safely, operate reliably, remain secure and compliant, and improve continuously over time. To ensure operational excellence it´s important to understand our customers needs and business.

What you'll do:

• Lead Managed AI capability development and provide guidance and mentorship to the team.

• Design and implement operational frameworks spanning cloud infrastructure, data foundations, and model serving layers.

• Design and implement end-to-end AI solutions to production deployment.

• Optimize LLM-powered applications and agentic systems integrated into real business processes and systems.

• Lead production readiness assessments: infrastructure architecture, data pipeline validation, security reviews, and model performance evaluation.

• Build monitoring and observability solutions for AI-specific metrics: model drift, data quality, inference latency, and cost tracking.

• Establish incident response procedures and escalation paths for AI systems.

• Optimize costs across compute, storage, API calls, and token usage.

• Ensure our solution is in line with client business objectives and strategy.

• Advise clients on governance, compliance, and security for production AI.

• Drive continuous improvement: infrastructure optimization, data pipeline refinement, model retraining, and prompt tuning based on real-world feedback.

• Stay curious about the fast-evolving AI landscape, and bring that insight into client projects.

What we're looking for:

We are looking for an experienced AI professional who understands what it takes to run AI in production – not just build it. Someone who has dealt with model management, cost & performance optimization, and building production level AI solutions.

We hope you recognize yourself in most of these:

• 3+ years of experience in AI/ML engineering, MLOps, with hands-on production deployment experience.

• Strong understanding of the full AI operations stack: cloud infrastructure, data pipelines, model serving, and application integration.

• Excellent communication and consulting skills – able to translate operational complexity into business terms for C-level stakeholders.

• Experience in product ownership, platform ownership and/or service management

• Experience with MLOps practices: CI/CD for ML, model monitoring, drift detection, retraining pipelines, and version control.

• Knowledge of GenAI operational challenges: RAG architectures, vector database scaling, token cost management, and LLM evaluation.

• Hands-on experience with cloud platforms (Azure, AWS, GCP) including infrastructure-as-code and container orchestration.

• Understanding of data operations: pipeline health, content freshness, governance compliance, and quality monitoring.

• Curiosity and drive to define best practices in an emerging field.

• Fluent in Finnish and English.

Relevant technologies:

• Platforms: Azure AI Foundry, Amazon Bedrock, Databricks, Snowflake

• MLOps: MLflow, Kubeflow, Weights & Biases, model registries

• LLMs and LLM middleware: GPT, Claude, open-source models, LiteLLM, vLLM

• Vector databases: Pinecone, pgvector

• Agent technologies: MCP, agent/workflow frameworks (LangGraph, LlamaIndex, Haystack, Magentic, Strands)

• Cloud platforms: Azure, AWS, GCP

• Infrastructure: Kubernetes, Terraform, Docker

• Observability: Prometheus, Grafana, Datadog, custom AI metrics

• Python, SQL

What we offer:

• A technically strong and collaborative community: You'll work alongside experienced data professionals who support each other, share insights, and aim for excellence in everything we do. Our culture values respect, autonomy, and peer-driven improvement.