Artificial Intelligence Engineer
Summary: The AI Engineer role involves designing, building, and deploying AI and generative AI features into live systems within a hybrid work environment in Cambridge. The position requires collaboration with product and engineering teams to create deployable AI solutions and ensure reliable deployments at scale. Candidates should have strong hands-on experience in AI/ML production and be comfortable working with cloud environments. The role is classified as inside IR35 and offers a competitive day rate.
Key Responsibilities:
- Design, build and deploy production-grade AI and generative AI features into live systems.
- Work closely with product and engineering teams to translate business problems into deployable AI solutions.
- Own model integration, evaluation and monitoring once features are live.
- Collaborate with MLOps and platform teams to keep deployments reliable at scale.
- Stay close to the latest LLM tooling and bring practical recommendations back to the team.
Key Skills:
- Strong hands-on experience building and shipping AI/ML features into production, not just prototypes.
- Solid Python and experience with modern LLM frameworks and APIs.
- Comfortable working in cloud environments (Azure, AWS or GCP).
- Experience with MLOps practices, model monitoring and evaluation.
- Strong communication skills, able to work directly with non-technical stakeholders.
Salary (Rate): £650 per day
City: Cambridge
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Job Title: AI Engineer
Industry: Technology / Financial Services
Contract Duration: 6 months, likely extension
Location: Cambridge (hybrid, 2-3 days onsite)
Day Rate: £550- £650per day (Inside IR35)
The Role:
- Design, build and deploy production-grade AI and generative AI features into live systems
- Work closely with product and engineering teams to translate business problems into deployable AI solutions
- Own model integration, evaluation and monitoring once features are live
- Collaborate with MLOps and platform teams to keep deployments reliable at scale
- Stay close to the latest LLM tooling and bring practical recommendations back to the team
Skills Needed:
- Strong hands-on experience building and shipping AI/ML features into production, not just prototypes
- Solid Python and experience with modern LLM frameworks and APIs
- Comfortable working in cloud environments (Azure, AWS or GCP)
- Experience with MLOps practices, model monitoring and evaluation
- Strong communication skills, able to work directly with non-technical stakeholders
Research indicates that men will apply to a role when they meet only 50-60% of the requirements, while women and other underrepresented groups often look for a 90-100% match. If this role excites you but you don't tick every single box, please still apply. We'd love to hear from you.
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