Provectus

Senior Principal Technical Solution Owner / Product Manager – AI & Data Platforms

Provectus

full-time

Posted on:

Location Type: Remote

Location: Serbia

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Job Level

Senior

Tech Stack

AirflowAWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformKafkaKubernetesMicroservices

About the role

  • Architect Product Strategy for Technical Platforms: Define product strategy for AI platforms, data infrastructure, and enterprise-scale data migration initiatives.
  • Drive AI/ML Product Development: Own end-to-end product lifecycle for GenAI applications leveraging LLMs, RAG architectures, Agentic frameworks, and multi-modal AI systems.
  • Manage Complex Data Platform Initiatives: Lead product planning for data lake/lakehouse implementations, warehouse modernizations, and cloud data platform migrations.
  • Execute Through Agile Delivery: Facilitate Agile ceremonies and maintain well-groomed backlogs with properly sized, technically detailed Features and Epic level stories.
  • Enable Technical Decision-Making: Conduct technical due diligence, proofs-of-concept, and spike solutions to validate approaches before full investment.

Requirements

  • Bachelor's degree in Technology or Business related field (Master's preferred).
  • 5-7+ years of experience in technical product management, solutions architecture, or software engineering.
  • 5+ years in product management roles with demonstrated end-to-end product ownership.
  • 3-5+ years of experience with AI/ML products, Generative AI, or data platform development.
  • 3-5+ years working in Agile/Scrum environments with strong command of Agile methodologies and ceremonies.
  • Deep understanding of cloud architectures (AWS, Azure, GCP) and modern data stack technologies.
  • AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen).
  • Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures.
  • Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery).
  • MLOps: Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment tracking.
  • Data Migration: Assessment methodologies, migration patterns, data validation, cutover strategies.
  • Development Practices: API design, microservices, containerization (Docker, Kubernetes), CI/CD pipelines.
Benefits
  • Lead top-tier engineering teams and cutting-edge agentic AI systems, enterprise AI platforms.
  • Shape how enterprises adopt AI — from strategy to architecture to delivery.
  • Grow within a team building modern AI-delivery practices, tools, and frameworks.
  • Remote-friendly culture with strong engineering, data, and consulting partnerships.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI platformsdata infrastructureenterprise-scale data migrationGenerative AIdata lakecloud data platform migrationsAgile methodologiesETL patternsAPI designmicroservices
Soft Skills
product ownershiptechnical decision-makingleadershipcommunicationcollaborationproblem-solvingstrategic thinkingorganizational skillsfacilitationbacklog management
Certifications
Bachelor's degreeMaster's degree