Coforge
Senior AI Engineer

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Role: Senior AI Engineer
Skills: AI solutions, LLMs, AI/ML and MLOps
Location: UK (Remote)
Type: Permanent
About the Role
We are at Coforge hiring for Senior AI Engineer with AI solutions, LLMs, AI/ML and MLOps
Job Duties & Responsibilities:
We are seeking a highly skilled Senior AI Engineer to join our UK-based Artificial Intelligence team. This is a fully remote, hands-on engineering role focused on designing, developing, and scaling real-world AI solutions — taking them from concept through to production deployment. The successful candidate will work embedded within the UK team, ideally operating within UK working hours, and will play a central role in delivering high-quality AI systems across document processing, automation, and business applications.
- Design, develop, and deploy production-ready AI solutions with a strong focus on Generative AI and LLM-based applications.
- Build and optimise document extraction and processing pipelines using LLMs.
- Develop and refine prompt engineering strategies to improve output accuracy, consistency, and reliability.
- Analyse and optimise AI workflows across cost, latency, and quality trade-offs, ensuring scalable and efficient solutions.
- Develop, test, and enhance features within AI systems to improve performance and meet evolving business requirements.
- Support the end-to-end lifecycle of AI solutions, from prototype through to production deployment and monitoring.
- Collaborate closely with global teams and stakeholders to align solutions with business goals, and communicate complex technical concepts clearly to non-technical audiences.
- Contribute to rollout and implementation, ensuring models perform effectively for specific business scenarios.
- Monitor and evaluate model performance in production, identifying and acting on opportunities for continuous improvement.
- Stay current with the latest advancements in Generative AI and LLM engineering, applying new approaches where they add value.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Work Experience and Education Requirements:
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, Engineering, Mathematics, or a related field.
- Minimum of 5 years of experience, with a strong focus on hands-on AI/ML engineering and delivery.
- Proven track record of building, deploying, and maintaining production-grade AI/ML systems in live environments, with measurable business impact.
- Strong proficiency in Python and relevant AI/ML libraries.
- Demonstrated ability to deliver end-to-end Generative AI solutions, including working with LLMs in production; fine-tuning pre-trained models for specific use cases; designing robust prompt engineering strategies; building document processing pipelines; and evaluating outputs using structured metrics and feedback loops.
- Experience designing scalable, high-performance AI systems with a focus on cost, latency, and quality trade-offs.
- Strong working knowledge of Git and agile delivery practices.
- Excellent problem-solving skills and attention to detail.
- Experience with LLM orchestration frameworks (e.g., Langhian).
- Knowledge of MLOps practices, including CI/CD, monitoring, and model lifecycle management.
- Experience with vector databases, embeddings, and retrieval-augmented generation (RAG).
- Familiarity with document intelligence, OCR, or structured data extraction solutions.
- Experience deploying AI solutions in enterprise or client-facing environments.
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