Описание
We believe in the power of ingenuity to build a positive human future. We challenge where it matters and own the outcome. We combine strategic thinking, customer-centric service design, and agile engineering practices to accelerate innovation in a tech-driven world.
Задачи
- Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem solve with our clients, as well as working on internal projects
- Live in-person whiteboarding sessions to problem solve as a team, alongside asynchronous communication on Teams
- Experimenting with Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic.
- Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs.
- Developing and testing agentic architectures through our own Genie Platform - enabling AI agents that reason, retrieve, and act across systems.
- Exploring LLMOps, evaluation tools, and model observability platforms like TruLens and LangSmith.
- Deploying solutions on modern cloud and DevOps environments (AWS, Azure, GCP) - but always choosing the right tools for the problem at hand.
- Constantly learning, testing, and sharing findings across our internal AI community.
Требования
- Software engineers with a passion for AI – or data scientists who’ve embraced engineering.
- People who experiment, prototype, and explore emerging AI tools in their own time.
- Strong foundation in a language suited to AI system development and data workflows.
- Experience integrating models with APIs, data sources, or production systems.
- Curiosity about LLMs, RAG pipelines (Graph & Vector based), and agent frameworks.
- Understanding of cloud-native (AWS / GCP / Azure) and DevOps / DevSecOps practices.
- A collaborative mindset and willingness to share, learn, and teach.
- Understanding of prompt and context engineering and model evaluation.
- Solid grasp of distributed systems, microservices, and RESTful APIs.
- An understanding of LLMOps tools for managing GenAI workflows.
Условия
- Hybrid working - our approach is to be in the office or on client site a minimum of 2 days per week.
- Grow a flexible and unique career within a trust-based, inclusive environment that values excellence, innovation, and curiosity.
- Work on a broad variety of projects and tech stacks for clients across seven sectors - no project is ever the same
- Join other experts within our supportive and collaborative tech community through knowledge-sharing and peer-level support, coaching and mentoring
- Deepen your expertise through our culture of learning and growth - you'll have budget to take courses (technical and non-technical training), plus gain certifications
- Hybrid working with the team on client site or in our office a minimum of two days per week. However, the actual time you spend and where you spend it will vary by role or assignment, including up to 5 days per week on a client site.
- Health and lifestyle perks accompanying private healthcare for you and your family
- 25 days annual leave (plus a bonus half day on Christmas Eve) with the opportunity to buy 5 additional days
- Generous company pension scheme
- Opportunity to get involved with community and charity-based initiatives
- Annual performance-based bonus
- PA share ownership
- Tax efficient benefits (cycle to work, give as you earn)
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AI engineer for LLM systems employer: PA Consulting
At PA Consulting, we pride ourselves on being an excellent employer that fosters a collaborative and innovative work culture. As a Data Architect, you will have the opportunity to lead transformative projects in a hybrid working environment, allowing for flexibility while engaging with clients and colleagues. We are committed to your professional growth, offering continuous learning opportunities and the chance to work on cutting-edge AI-driven data solutions that make a real impact.
