Senior AI Engineer – (Manager) BIP xTech

Overview

In this role you design, build and run production-grade AI solutions end-to-end, from use-case to deployment and monitoring. You shape architectures for AI systems, lead AI/ML workstreams, and mentor engineers while ensuring responsible AI and governance. You collaborate closely with data engineers and software teams to deliver coherent platforms and support business development with technical insights. This is a chance to influence AI delivery at scale within BIP xTech’s Centre of Excellence, driving measurable business value.

Pay / Benefits

• Hybrid working
• Frontier AI delivery exposure
• Culture that encourages innovation
• Ownership of work
• Growth opportunities in AI Centre of Excellence

Responsibilities

• Design, develop, and deploy production-grade AI/ML solutions including GenAI and LLM-enabled systems
• Shape AI solution architectures (batch vs streaming, RAG, feature stores, model serving)
• Lead AI/ML workstreams end-to-end (planning, governance, stakeholder management)
• Mentor AI engineers, data scientists, and software engineers
• Implement secure, scalable deployment patterns aligned with governance and Responsible AI
• Embed monitoring, evaluation, and continuous improvement across AI solutions
• Collaborate with Data Engineers, Cloud/Data Architects, and Software Engineers to deliver coherent platforms
• Contribute to pre-sales, discovery, and proposal development by shaping options and delivery approaches
• Build relationships with clients and partners as a trusted technical advisor

Key requirements

• 3+ years delivering AI/ML solutions in production
• Experience delivering GenAI and LLM-based solutions from prototype to production
• Strong Python engineering skills with focus on quality and maintainability
• Foundations in ML concepts, evaluation techniques, and statistics
• Experience with Databricks and one or more cloud platforms (Azure, AWS, or GCP)
• Security-by-design knowledge (access control, secrets management, secure networking)
• Ability to align AI solutions with governance, compliance, and Responsible AI requirements
• Proven experience leading delivery and coordinating multidisciplinary engineering teams

• Leadership and mentoring
• Stakeholder management
• Collaboration across cross-functional teams
• Python engineering
• GenAI and LLM technologies
• ML concepts and evaluation

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