Description
About Baringa
Baringa is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding.
The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence – all powered by advanced technology, data, AI and digital innovation.
Clients value Baringa’s collaborative approach and the way its teams integrate seamlessly – all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors.
Certified as a Great Place to Work around the world, Baringa has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World’s Best Management Consulting Firms.
Our Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability.
The AI/ML Senior Manager role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep technical specialism with the commercial and leadership skills to grow and shape our practice.
This is a role for someone who thrives at the intersection of client advisory, technical architecture and hands-on delivery leadership – and who has a genuine passion for bringing AI solutions to production at scale.
Our Solutions & AI Labs (SAIL) practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions.
What you will be doing
As a Senior Manager in SAIL, you will own and lead consultancy engagements end-to-end from shaping the opportunity and winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients.
Although we do not expect you to be an expert in all of the below activities simultaneously, our team consists of people who can work as advisors to our clients as well as bringing deep technical knowledge when needed. The profile of our typical engagements reflects that.
Key responsibilities span the following areas.
Engagement Leadership:
- Own and lead end-to-end delivery of complex AI and technology consulting engagements, taking accountability for scope, quality, risk and client outcomes.
- Lead and resource multi-disciplinary delivery teams including engineers, data scientists and consultants providing clear direction, technical oversight and people development.
- Manage engagement resourcing: forecast team requirements, work with practice leadership to staff engagements, and develop the talent pipeline through mentoring and support of junior practitioners.
- Proactively identify and manage delivery risks in complex stakeholder environments, escalating appropriately and maintaining client confidence throughout.
- Communicate clearly to both technical teams and senior client stakeholders, translating complexity into actionable insight and decisive recommendation.
- Conduct rigorous technical reviews and uphold engineering and delivery standards across every engagement you lead.
Business Development & Bid Support:
- Play a leading role in business development: identifying new opportunities, shaping propositions, and supporting or leading bids and tender responses for AI and technology engagements.
- Contribute to proposal writing, articulating Baringa’s capabilities and differentiators, including authoring technical and delivery sections of bid responses to client tenders and RFPs.
- Build and maintain strong client relationships, acting as a trusted advisor and developing opportunities for follow-on engagement.
- Support practice-level growth initiatives, including account planning, capability development, and go-to-market positioning for AI and solutions engineering services.
Technical Architecture & Delivery:
- Lead architecture design for AI-enabled platforms and cloud solutions, balancing technical excellence with delivery pragmatism and commercial realities.
- Provide hands-on technical direction where required – reviewing designs, code and delivery artefacts to maintain quality standards across the engagement.
- Champion the path from prototype to production: driving robust, scalable and secure AI deployments that go beyond proof-of-concept thinking to real business impact at scale.
- Act as a credible technical voice with client architects, CTOs and engineering leads, earning trust through depth of knowledge and a demonstrable delivery track record.
AI/ML Specialism
You will bring expert-level knowledge in at least one of the following domains, and working knowledge across the others:
Agentic AI & LLM Engineering:
- Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale.
- Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks.
Machine Learning Engineering:
- End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection.
- Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI).
Software Engineering:
- Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js, Material UI and SWR.
- Cloud architecture design capability across major providers; rounded understanding of database trade-offs – relational, NoSQL, graph and caching strategies.
- Strong engineering practices: CI/CD, testing (Jest, Cypress, React Test Library), release management and security-conscious d
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