2 months ago
London, United KingdomStaff+
Responsibilities
- Lead end-to-end solution development, technical strategy, design quality, and roadmaps for multiple enterprise Agentic AI deployments.
- Serve as the primary technical point of contact from integration design through post-deployment optimization.
- Translate ambiguous customer requirements into engineering plans with milestones and success criteria.
- Customize and extend platform components, APIs, tooling, and bespoke logic.
- Architect scalable and compliant Agentic AI solutions, including multi-agent orchestration, RAG pipelines, and LLM/SLM integrations.
- Champion observability, telemetry, auditable AI standards, reusable frameworks, and asset libraries.
- Build and guide cross-functional Forward Deployed Engineering teams and coach senior and junior engineers.
- Provide structured product feedback and contribute to playbooks, best practices, and technical blog posts.
Requirements
- 8–12+ years of engineering experience, including 3+ years in customer-facing or Forward Deployed Engineer roles.
- Proven experience deploying AI/ML or data-intensive applications in production.
- Strong full-stack skills with Python, Node.js or Go, React or Vue, SQL, REST, and GraphQL.
- DevOps proficiency with Docker, Kubernetes, CI/CD, and major cloud platforms.
- Expertise in LLMs, prompt engineering, vector databases, RAG pipelines, and Agentic orchestration frameworks.
- Experience with MCP and enterprise integrations such as Salesforce or SAP.
- Excellent communication with technical and executive stakeholders plus demonstrated mentorship ability.
- Bachelor’s, master’s, or doctoral degree in Computer Science, Data Science, or a related field.
- Preferred qualifications include SLM fine-tuning or distillation experience, hands-on use of Agentic AI platforms such as Agentforce or Copilot Studio, AI compliance knowledge, and open-source or research contributions to LangChain, RAG, or Knowledge Graph communities.
