Senior Manager, Forward Deployed AI Engineer

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.

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 (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; experienced with containerisation, IaC, event‑driven architectures and CI/CD. Track record of delivering production Python services and APIs; working knowledge of cloud‑native application patterns and release practices.
• 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 development.

A genuine passion for AI solutions and specifically for the complexity of delivering them to production at scale; energized by operationalisation, reliability and governance as well as technology.

Your Skills And Experience

• 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.
• Proven ability to build and lead high‑performing delivery teams in complex stakeholder environments, with experience engaging comfortably at CTO or engineering director level.
• Clear, confident communicator – able to make the complex accessible for technical and non‑technical audiences alike, and to represent Baringa’s expertise with credibility.
• 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.