1 day ago
Bristol, United KingdomMid Level
Responsibilities
- Support the design of end-to-end AI pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
- Assist with designing and documenting agentic AI systems, including tool use, orchestration, memory and context management, and LLM integration.
- Support integration of AI and ML solutions with existing platforms and applications.
- Develop knowledge of MLOps practices including retraining, model versioning, drift detection, and rollback procedures.
- Contribute to technical proposals, architecture diagrams, and solution documentation for bids and pre-sales engagements.
- Research tooling, platform, and hosting options and communicate architectural trade-offs.
- Identify technical risks involving data quality, model drift, integration failures, AI security, and safety.
- Work with ML engineers, data engineers, and domain specialists to incorporate technical constraints into solution designs.
- Develop understanding of how AI solutions are scoped, costed, planned, and assured across programmes.
- Take increasing ownership of discrete solution components as experience develops.
Requirements
- Hands-on experience building, training, and deploying AI or ML models as an AI or ML engineer.
- Working knowledge of at least one of agentic AI and LLM application patterns, ML model serving and monitoring, data pipeline design, or MLOps practices.
- Ability to consider the wider system and purpose of a solution beyond implementation details.
- Clear written and verbal communication skills for explaining technical concepts to varied audiences.
- Curiosity, self-direction, and willingness to develop beyond a current specialism.
- Awareness of AI security and safety principles, including secure data handling, access control, and model risk.
- Eligibility for SC clearance is required.
- Exposure to medallion or lakehouse data platform architectures is desirable.
- Hands-on experience with MLOps tooling or model-serving infrastructure is desirable.
- Experience contributing to technical documentation, proposals, or solution designs is desirable.
- Familiarity with edge deployment or resource-limited inference environments is desirable.
- Experience in secure, regulated, or government-adjacent environments is desirable.
Benefits
- Flexible hybrid working, typically averaging three days in the office each week depending on the role.
- Part-time working requirements and workplace adjustments are supported where possible.
- Structured mentorship and development toward broader solution architecture ownership.
- Inclusive workplace with support for applicants with disabilities and health conditions.
Categories
Solutions Engineering
About Rowden
Rowden builds mission-critical, real-time edge computing systems that turn advances in sensing, AI, and communications into operational capability in degraded or denied environments. It provides systems integration, software, and technology services to national security, defense, and critical industry customers, improving decision-making for frontline teams. Founded in 2017 and headquartered in Bristol, England, the privately held company operates over 20,000 square feet of engineering and manufacturing facilities.