Dieses Stellenangebot ist nicht mehr verfügbar
AI Solutions Engineer
ARM
- London, England, United Kingdom
- London, England, United Kingdom
Über
London based - hybrid working - 2/3 days on site
Job Description Summary This hands‑on role requires deep expertise in artificial intelligence, machine learning, and software development to design, build, and deploy advanced Agentic AI‑driven solutions tailored to clients' unique needs. The Agentic AI Solutions Engineer will focus on implementing intelligent agents and leveraging AI technologies to streamline and enhance business operations, delivering measurable value and aligning closely with strategic goals. The Agentic AI Solutions Engineer will be instrumental in advancing the organization's research and development capabilities. This includes investigating the latest developments in agentic AI and machine learning, experimenting with novel approaches, and transforming research insights into working prototypes. The role also involves maintaining and evolving our product portfolio of Agentic AI Agents, as well as designing and developing compelling demos to showcase innovations.
Key Responsibilities
Develop, fine‑tune, and deploy AI models, including large language models (LLMs) such as GPT‑4 or open‑source equivalents.
Design and implement effective prompt engineering strategies and optimizations to enhance AI accuracy, consistency, and reliability.
Rapidly prototype, test, and iterate AI applications using advanced Python programming and relevant frameworks.
Integrate AI solutions securely with existing enterprise systems (CRM, ERP, HRIS, finance platforms, collaboration software) via API development and integration.
Build, maintain, and optimize end‑to‑end data pipelines to ensure accurate and timely data delivery for AI models.
Manage structured and unstructured datasets, leveraging vector databases and semantic search to enhance knowledge management capabilities.
Deploy, manage, and scale AI solutions within cloud computing environments (Azure, AWS, GCP), ensuring high availability, performance, and cost efficiency.
Implement DevOps and MLOps practices, including automated deployment, testing, monitoring, and version control, to efficiently manage the model lifecycle.
Identify and mitigate risks associated with AI deployments, proactively addressing ethical considerations, biases, and unintended consequences.
Knowledge and Attributes
Deep understanding of artificial intelligence, natural language processing (NLP), and machine learning principles.
Expertise in selecting, fine‑tuning, and deploying large and small language models (LLMs/SLMs), such as OpenAI's GPT series and open‑source alternatives.
Proven experience with prompt engineering, prompt optimization, and AI model reliability and accuracy improvements.
Advanced proficiency in Python programming, essential for rapid prototyping, integration, and model implementation. Python is the preferred language for AI; strong proficiency in Python is essential due to the extensive use of frameworks, libraries, and models.
Knowledge of additional programming languages:
JavaScript / TypeScript: Helpful if building frontend interfaces or web integrations.
Java / C#: Beneficial for integrations with enterprise backend systems (e.g., ERP, CRM).
Strong experience developing APIs and integrating AI solutions securely with enterprise systems and applications.
Familiarity with full‑stack software development, including frontend and backend integration, user experience considerations, and system interoperability.
Robust knowledge of data pipeline development, data engineering concepts, and handling of structured and unstructured data.
Experience with vector databases and semantic search tools for effective knowledge management.
Proficiency in cloud computing platforms (Azure, AWS, GCP), particularly in deploying, scaling, and managing AI workloads.
Solid understanding and experience implementing DevOps and MLOps practices, automated model lifecycle management, and continuous integration/deployment.
Experience with Microsoft Copilot Studio, Azure AI Foundry, and Semantic Kernel is highly desirable.
Awareness and application of security, compliance, and risk management practices related to AI solutions.
Required Experience
Proven experience developing, deploying, and maintaining AI and machine learning solutions in enterprise environments.
Strong hands‑on expertise in AI model development, fine‑tuning, and optimization using Python and relevant frameworks.
Demonstrated experience implementing prompt engineering methodologies and optimizing model performance.
Solid experience in API development and secure integration of AI‑driven solutions with enterprise systems and platforms.
Experience building robust data pipelines, managing structured/unstructured data, and leveraging vector databases.
Practical experience deploying and scaling AI applications within cloud platforms (Azure, AWS, or GCP).
Demonstrated success applying DevOps and MLOps best practices to manage AI model lifecycle and deployments efficiently.
Proven track record ensuring security, privacy, compliance, and responsible use of AI solutions within regulated environments.
Disclaimer This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today.
#J-18808-Ljbffr
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot wurde von einem unserer Partner veröffentlicht. Sie können das Originalangebot einsehen hier.