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Endava

AI Engineer

Endava

Published 25 Nov 2025
Singapore
Full Time

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Role Highlights

Languages used

Python
SQL

Key skills

Machine Learning
Data Science
Deep Learning
ML Ops
Reinforcement Learning
Prompt Engineering
Computer Science
API
Technical Leadership
Cloud
LLMs
RAG
Mathematics
Quantitative
Regression
Clustering
Deployment

Tools, Libraries and Frameworks

Vertex AI
GCP
Docker
Kubernetes
AWS
Azure
Tensorflow
PyTorch
LLamaindex
Scikit-learn
React
Langchain
Pandas
NumPy
FastAPI
Flask

Description

Endava AI Engineer \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . AI Engineer Full-time Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. Job Description Are you passionate about translating complex business challenges into cutting-edge AI solutions? We're seeking a hands-on AI/ML Engineer / Senior Engineer to join our team. This role is at the cutting edge of applied AI - it's an opportunity to be a core builder. You will be responsible for designing, developing and deploying AI agents leveraging Googles Vertex AI ecosystem and building solutions that around sophisticated machine learning models to cutting-edge Agentic AI for our clients. The ideal candidate should have hands-on experience with machine learning algorithms, deep learning frameworks, and cloud-based ML solutions (preferably on Google Cloud stack). What You'll Design & Own Design End-to-End AI Solutions: Translate complex business problems into scalable, secure, and robust technical architectures. You will be the primary designer for solutions leveraging Agentic AI, LLMs, and advanced RAG. Build and fine-tune agentic logic using Google's Gemini models and the Vertex AI platform. Develop sophisticated prompting strategies (e.g., ReAct, CoT) and evaluation frameworks. Get your hands dirty. Write high-quality, efficient code to build and train machine learning models and complex AI systems. Be a key player in developing innovative Agentic AI solutions, creating systems that can reason, plan, and act on complex tasks. Own the full model lifecycle. You will be responsible for deploying models into production environment, monitoring their performance, and iterating (MLOps). Qualifications We are looking for a blend of technical depth, engineering rigor, and creative problem-solving. Hands-on experience in building and deploying machine learning models. Bachelors or Masters degree in Computer Science, Engineering, Mathematics, Data Science, AI, or a related quantitative field. Programming: Expert-level proficiency in Python. ML Frameworks: Deep, practical experience with ML libraries like Scikit-learn, TensorFlow, and/or PyTorch and ML algorithms like classification, regression, clustering, reinforcement learning. GenAI & Agentic AI: Demonstrable experience with Large Language Models (LLMs), prompt engineering, and frameworks like LangChain, LlamaIndex, or similar. Data Stack: Strong skills in data manipulation and analysis using SQL, Pandas, and NumPy. Deployment & MLOps: understanding of MLOps principles. Hands-on experience with containerization (Docker, Kubernetes) and deploying models as scalable APIs (e.g., FastAPI, Flask). Cloud Experience: experience building and deploying solutions on at least one major cloud platform (GCP (Preferred), AWS, or Azure). Desirable Skills Experience designing multi-agent systems or autonomous workflows. Hands-on experience with Google Cloud Platform. Publications, conference speaking, or open-source contributions in the AI/agent space. Additional Information Discover some of the global benefits that empower our people to become the best version of themselves: Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus; Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership; Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences; Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme; Health: Global internal wellbeing programme, access to wellbeing apps; Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations. At Endava, were committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectivesbecause we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know. I'm interested I'm interestedCookies Settings I'm interested Refer a friend share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. AI Engineer Singapore Full-time I'm interested I'm interested

Required Qualifications and Skills

The role requires expert-level proficiency in Python programming. Candidates must possess deep, practical experience with ML libraries such as Scikit-learn, TensorFlow, and/or PyTorch, along with an understanding of ML algorithms like classification, regression, clustering, and reinforcement learning. Demonstrable experience with Large Language Models, prompt engineering, and frameworks like LangChain or LlamaIndex is necessary. Strong skills in data manipulation and analysis using SQL, Pandas, and NumPy are also required. Experience with MLOps principles, containerization (Docker, Kubernetes), and deploying models as scalable APIs (e.g., FastAPI, Flask) is expected. A Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Data Science, AI, or a related quantitative field is sought.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Endava

Size

10278

HQ

London, GB

Public/Private

Public Company

Description

Endava is reimagining the relationship between people and technology. We have helped some of the worlds leading Payments, Financial Services, Telecommunications, Media, Technology, Consumer Products, Retail, Mobility, and Healthcare companies accelerate their ability to take advantage of new business models and market opportunities. By ideating and delivering dynamic platforms and intelligent digital experiences, we help our clients fuel the rapid, ongoing transformation of their business. By leveraging next-generation technologies, our agile, multi-disciplinary teams provide a combination of Product & Technology Strategies, Intelligent Experiences, and World Class Engineering to help our clients become more engaging, responsive, and efficient. Endava has 11,761 people as of September 30, 2023, located in the European Union: Austria, Bulgaria, Croatia, Denmark, Germany, Ireland, Netherlands, Poland, Romania, Slovenia and Sweden; Non-European Union: Bosnia & Herzegovina, Moldova, North Macedonia, Serbia, Switzerland and the United Kingdom; North America: Canada and the United States; Latin America: Argentina, Colombia, Mexico and Uruguay; Asia Pacific: Australia, Malaysia, Singapore

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