Applied AI Engineer

About Us

At Validata, our mission is to be the trusted partner for digital transformation success, helping banks, corporates and financial institutions with continuous quality engineering and automation, smart ‘progressive’ data migration, real-time end-to-end reconciliations, and payments

transformation—including ISO 20022 readiness—to reduce risk, improve quality, and enable faster go-lives.

The Role

Validata is growing, and we’re looking for a highly skilled Applied AI Engineer to drive the technical delivery of AI solutions for mission-critical banking environments. Working closely with Product, you’ll translate customer requirements into technical priorities, with hands-on responsibility for model selection, agent architecture, RAG pipelines and deployment.

Leading a small engineering team, you’ll be pioneering AI capabilities from experimentation to production, building LLM systems, reusable APIs and agentic workflows that automate complex financial tasks with the accuracy, security and reliability the banking and payments industry demands.

Responsibilities

• Define and drive Validata’s agentic AI roadmap into technical designs and delivery plans aligned with customer needs and business outcomes
• Lead agile innovation cycles from ideation through proof of concept, MVP, and go-to-market
• Architect and build multi-agent systems, covering role definition, tool integration, planning, memory and workflow orchestration
• Build and optimise RAG pipelines and semantic search using vector databases, including indexing, retrieval policies, and evaluation
• Integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems, with robust error handling and output validation
• Design evaluation frameworks to systematically assess agent performance across key operational metrics
• Apply advanced prompt and context engineering and implement guardrails to reduce hallucinations
• Deploy scalable AI services to cloud infrastructure with full observability and monitoring
• Build microservices-based architectures and instrument agents for tracing, metrics, and continuous improvement
• Partner with product teams and stakeholders to shape requirements and deliver intuitive human AI interfaces (voice, chat)
• Use data analysis to improve agent capabilities, optimise retrieval and inform technical decisions
• Establish engineering standards through code reviews, testing, documentation and reusable components
• Mentor and upskill team members on agent frameworks, LLM best practices, and AI safety

Experience and Qualifications

• Degree in Computer Science, Data Science, Machine Learning or a related field, or equivalent practical experience; an MSc or PhD is a plus
• Proven experience building and deploying production AI/ML applications in FinTech, banking, payments or financial services
• Strong Python skills and experience with relevant ML frameworks, such as PyTorch, TensorFlow or scikit-learn
• Hands-on experience building LLM applications using agentic frameworks and generative models
• Experience developing RAG pipelines, semantic search and vector database integrations
• Familiarity with cloud platforms such as AWS, Azure or GCP, and containerisation technologies including Docker and Kubernetes
• Experience designing reliable APIs, microservices and integrations with external systems
• Familiarity with prompt optimisation frameworks and evaluation suite design
• Experience fine-tuning small language models using LoRA, QLoRA or DoRA is desirable; quantisation and distillation experience is a plus
• Relevant Claude certifications are highly advantageous
• Experience providing technical leadership, mentoring engineers and coordinating delivery
• Ability to make sound architectural decisions, communicate trade-offs and unblock technical work
• Strong written and verbal English, with the ability to explain technical concepts to engineering and business stakeholders
• A practical approach to problem-solving and the ability to prioritise in a fast-paced environment

Further advantages:

• Familiarity with banking, payments, reconciliation, data migration or quality engineering
• Knowledge of data visualisation tools is a plus
• Familiarity with front-end technologies is a plus

Benefits

• Highly competitive salary, plus additional benefits and perks
• Holiday and vacation allowance
• A challenging role with meaningful ownership and impact
• Work in an agile environment on high-profile banking projects
• Flexible working built around you — choose remote, hybrid, or onsite, with the freedom to adapt your schedule and setup to what helps you do your best work
• A long-term, challenging role with meaningful ownership and impact
• Growth is a priority: we invest in your development with continuous learning and mentorship to build the skills that move your career forward
• Join a supportive, collaborative team where knowledge is shared, wins are celebrated, and you’re set up to thrive

Equal Employment Opportunity Policy

Validata Group is an equal opportunity employer. We provide equal employment opportunities to all applicants and employees, and we’re committed to an inclusive workplace where everyone is treated with dignity, respect and diverse perspectives are truly valued.

If this sounds interesting and you think we might “click”, please apply!

Please apply via the link below:

https://validatasoftware.peopleforce.io/careers/v/251123-applied-ai-engineer

Explore more career opportunities at Validata here:

https://validatasoftware.peopleforce.io/careers