Summary: The AI Engineer role at emagine involves designing, building, and deploying agentic AI solutions, requiring deep expertise in Python, LangGraph, and LangChain. The position is based in London with a hybrid working arrangement, focusing on enterprise-grade AI applications across Azure and AWS. The successful candidate will engage in cutting-edge AI initiatives and collaborate with various stakeholders to deliver innovative solutions. This is an initial 6-month engagement classified as inside IR35.
Key Responsibilities:
- Design, develop, and deploy scalable agentic AI solutions using Python, LangGraph, and LangChain.
- Build and manage multi-agent architectures, including agent orchestration, coordination, and workflow management.
- Implement advanced AI capabilities including:
- Retrieval-Augmented Generation (RAG)
- Memory management
- Planning and reasoning frameworks
- Human-in-the-loop workflows
- Tool integration and Model Context Protocol (MCP) integration
- Develop and optimise prompts, agent behaviours, and decision-making processes through effective prompt engineering and evaluation methodologies.
- Establish robust guardrails, governance frameworks, and responsible AI practices.
- Implement observability, monitoring, testing, and performance evaluation for AI systems.
- Build and maintain CI/CD pipelines for AI application deployment and life cycle management.
- Ensure security, scalability, and reliability of AI solutions in enterprise environments.
- Integrate AI agents with enterprise APIs, data platforms, business applications, and cloud services across Azure and AWS.
- Collaborate with architects, engineers, product teams, and business stakeholders to deliver innovative AI-driven solutions.
Key Skills:
- Minimum 8 years of hands-on experience building AI solutions, with significant experience in agentic AI development.
- Strong proficiency in Python.
- Extensive experience with LangGraph and LangChain.
- Proven expertise in:
- Agent orchestration
- Multi-agent systems and workflows
- Tool and MCP integration
- Retrieval-Augmented Generation (RAG)
- AI memory architectures
- Planning and reasoning frameworks
- Human-in-the-loop systems
- Deep understanding of multi-cloud environments, particularly Microsoft Azure and Amazon Web Services (AWS).
- Experience implementing prompt engineering, evaluation frameworks, guardrails, and AI governance.
- Strong knowledge of observability, monitoring, testing, and quality assurance for AI systems.
- Experience with CI/CD, DevOps practices, and secure software deployment.
- Demonstrated ability to integrate AI solutions with enterprise platforms, APIs, and data ecosystems.
- Excellent communication and stakeholder management skills.
Salary (Rate): £600pd
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
AI Engineer
£600pd Inside IR35
2-3 days on site in London
Initial 6 month engagement
emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high-end consulting services and solutions.
We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication in delivering the optimal service for our clients. Our commitment is not just towards our clients but we aim to foster a positive and equitable working environment with our consultants and colleagues which stems from our core values: Confident, Dedicated, Responsible, Genuine.
We are seeking an experienced AI Engineer with a proven track record of designing, building, and deploying agentic AI solutions. The successful candidate will have deep hands-on expertise in Python, LangGraph, and LangChain, alongside strong experience delivering enterprise-grade AI applications across Azure and AWS cloud environments.
This is an exciting opportunity to work on cutting-edge AI initiatives involving autonomous agents, multi-agent systems, retrieval-augmented generation (RAG), and advanced orchestration frameworks that drive real business value.
Key ResponsibilitiesDesign, develop, and deploy scalable agentic AI solutions using Python, LangGraph, and LangChain.
Build and manage multi-agent architectures, including agent orchestration, coordination, and workflow management.
Implement advanced AI capabilities including:
Retrieval-Augmented Generation (RAG)
Memory management
Planning and reasoning frameworks
Human-in-the-loop workflows
Tool integration and Model Context Protocol (MCP) integration
Develop and optimise prompts, agent behaviours, and decision-making processes through effective prompt engineering and evaluation methodologies.
Establish robust guardrails, governance frameworks, and responsible AI practices.
Implement observability, monitoring, testing, and performance evaluation for AI systems.
Build and maintain CI/CD pipelines for AI application deployment and life cycle management.
Ensure security, scalability, and reliability of AI solutions in enterprise environments.
Integrate AI agents with enterprise APIs, data platforms, business applications, and cloud services across Azure and AWS.
Collaborate with architects, engineers, product teams, and business stakeholders to deliver innovative AI-driven solutions.
Minimum 8 years of hands-on experience building AI solutions, with significant experience in agentic AI development.
Strong proficiency in Python.
Extensive experience with LangGraph and LangChain.
Proven expertise in:
Agent orchestration
Multi-agent systems and workflows
Tool and MCP integration
Retrieval-Augmented Generation (RAG)
AI memory architectures
Planning and reasoning frameworks
Human-in-the-loop systems
Deep understanding of multi-cloud environments, particularly Microsoft Azure and Amazon Web Services (AWS).
Experience implementing prompt engineering, evaluation frameworks, guardrails, and AI governance.
Strong knowledge of observability, monitoring, testing, and quality assurance for AI systems.
Experience with CI/CD, DevOps practices, and secure software deployment.
Demonstrated ability to integrate AI solutions with enterprise platforms, APIs, and data ecosystems.
Excellent communication and stakeholder management skills.
Experience with enterprise-scale AI deployments and production-grade agent frameworks.
Knowledge of vector databases, knowledge graphs, and advanced retrieval techniques.
Familiarity with MLOps and AI governance best practices.
Experience working within highly regulated environment
Interested?
At emagine, we are committed to building an international and diverse team by embracing our different backgrounds.
If you are up to the challenge and would like to find out more, get in touch with us immediately, our internal recruitment team is always keen to hear from dynamic individuals that are looking to further their career and explore their full potential.
emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin