At a Glance
- Tasks: Lead AI consultancy projects and deliver innovative solutions for clients.
- Company: Join a forward-thinking tech firm focused on AI and solutions engineering.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative culture that values technical excellence and human connection.
- Why this job: Make a real impact by bringing AI solutions to life at scale.
- Qualifications: 7+ years in tech consulting with expertise in AI/ML or software engineering.
The predicted salary is between 80000 - 100000 £ per year.
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 Forward Deployed AI & Solutions Engineer 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.
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.
- 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.
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.
- Support practice-level growth initiatives, including account planning, capability development, and go-to-market positioning for AI and solutions engineering services.
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.
AI/ML Specialism:
- Agentic AI & LLM Engineering: 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).
- Platform & Cloud Engineering: Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure or GCP; Track record of delivering production Python services and APIs.
- Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js, Material UI and SWR.
- Rounded understanding of database trade-offs – relational, NoSQL, graph and caching strategies.
- CI/CD, testing (Jest, Cypress, React Test Library), release management and security-conscious development.
A genuine passion for AI solutions and specifically for the complexity of delivering them to production at scale. We're seeking a technically credible, commercially aware leader who brings a rare combination of delivery accountability, client advisory skill, and deep AI/technology specialism. You will be someone energised by the complexity of taking AI solutions to production at scale – and who can inspire a team and a client with that same passion.
- 7+ years in technology consulting, software engineering or AI/ML, with at least 3 years in a senior leadership role – including direct accountability for end-to-end engagement delivery, resourcing and commercial outcomes.
- Experience supporting or leading bid and proposal activity, including writing technical and delivery sections of responses to client tenders and RFPs.
- SME-level depth in at least one of: Agentic AI/LLM Engineering, Machine Learning Engineering, Platform & Cloud Engineering, or Software Engineering – with strong architecture and design capability across cloud, data and AI domains.
- Master's degree in Computer Science, Engineering, Mathematics, Data Science or related discipline, or equivalent depth through relevant professional certifications (e.g. AWS Solutions Architect Professional, Google Professional ML Engineer).
- Desirable: prior experience as a forward-deployed or embedded engineer within a client environment; exposure to regulated industries such as energy, financial services or public sector.
If you are excited by the opportunity to lead meaningful AI and technology engagements for major clients and thrive in a collaborative, people-first culture that values both technical rigour and human connection we would love to hear from you.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed AI Engineer, Senior Manager in Bristol
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We think you need these skills to ace Forward Deployed AI Engineer, Senior Manager in Bristol
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Baringa Partners, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Baringa Partners. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Baringa Partners
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Baringa Partners!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
