Senior Principal Technical Solution Owner, AI & Data Platforms
Provectus
full-time
Posted on:
Location Type: Remote
Location: United Kingdom
Visit company websiteExplore more
Job Level
About the role
- Define product strategy for AI platforms, data infrastructure, and enterprise-scale data migration initiatives.
- Lead technical product discovery – evaluating emerging technologies (GenAI, Agentic AI, vector databases, streaming architectures) and assessing fit for client use cases.
- Design solution architectures in collaboration with data architects and engineers, making build-vs-buy decisions and technology stack selections.
- Develop technical roadmaps balancing innovation, scalability, security, and time-to-value.
- Own end-to-end product lifecycle for GenAI applications leveraging LLMs, RAG architectures, Agentic frameworks, and multi-modal AI systems.
- Translate business requirements into technical specifications, API contracts, data schemas, and system integration patterns.
- Guide model selection, evaluation criteria, and deployment strategies for ML models in production environments.
- Champion MLOps practices including model versioning, monitoring, performance tracking, and continuous improvement loops.
- Lead product planning for data lake/lakehouse implementations, warehouse modernizations, and cloud data platform migrations.
- Define data product requirements including ingestion pipelines, transformation logic, data quality rules, governance policies, and access patterns.
- Oversee integration of multiple data domains, ensuring interoperability, data lineage, and metadata management.
- Partner with data engineering teams on performance optimization, cost management, and scalability planning.
- Facilitate Agile ceremonies and maintain well-groomed backlogs with properly sized, technically detailed Features and epic-level stories.
- Work closely with engineering teams to decompose complex features into incremental releases with clear technical dependencies.
- Define sprint goals aligned with quarterly objectives and long-term product vision.
- Balance technical debt management with feature delivery, advocating for enablers and architectural improvements.
- Conduct technical due diligence, proofs-of-concept, and spike solutions to validate approaches before full investment.
- Analyze trade-offs between competing technical solutions, considering performance, cost, maintainability, and developer experience.
- Document technical decisions, architectural decision records (ADRs), and design patterns for knowledge sharing.
- Communicate technical strategies and recommendations to executive stakeholders with clarity and conviction.
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.
- Solution design and technical architecture capabilities.
- Requirements translation from business needs to technical specifications.
- Strong analytical thinking and problem-solving in complex technical domains.
- Exceptional stakeholder management across technical and non-technical audiences.
- Clear technical communication—documenting complex systems and presenting architectural decisions.
- Risk identification, dependency mapping, and mitigation planning.
- Prior software development or data engineering experience (3+ years).
- Background in consulting or professional services, delivering client solutions.
- Certifications: AWS Solutions Architect, Azure Data Engineer, GCP Professional Data Engineer, Certified Scrum Product Owner.
- Insatiable curiosity about emerging technologies and a hands-on experimentation mindset.
- Close attention to detail with quality focus and commitment to technical excellence.
- Collaborative team player who thrives in cross-functional environments.
- Adaptable and comfortable navigating ambiguity in fast-paced consulting contexts.
- Passion for mentoring engineers and elevating technical practices.
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
AI platformsdata infrastructureenterprise-scale data migrationGenerative AIMLOpsETLdata modelingAPI designcloud architecturesAgile methodologies
Soft skills
analytical thinkingproblem-solvingstakeholder managementtechnical communicationcollaborative team playeradaptabilitymentoringrisk identificationdependency mappingattention to detail
Certifications
AWS Solutions ArchitectAzure Data EngineerGCP Professional Data EngineerCertified Scrum Product Owner