Posted on: 30/04/2026
Job Description :
We are seeking an experienced Senior AI Engineer to join our dynamic team, driving innovation in AI-driven solutions with a global impact. This role is specifically tailored for a highly motivated professional with a strong technical background in Python, hands-on expertise in developing Retrieval-Augmented Generation (RAG)-based applications, Machine Learning, Deep Learning, and solid cloud AI deployment experience across AWS and Azure.
As our Senior AI Engineer, you will spearhead the end-to-end development lifecycle, including solution architecture, design, implementation, deployment, and scaling of cutting-edge AI applications. Your leadership will ensure the delivery of high-performance, reliable, and impactful solutions.
What You Will Do :
- AI & ML Solution Delivery : Lead the end-to-end design and delivery of high-impact AI/ML solutions spanning RAG pipelines, LLM-based applications, and extraction systems with a focus on accuracy, scalability, cost-efficiency, and production-grade robustness.
- Technical Execution : Architect and develop robust, scalable AI/ML services in Python, ensuring reliability, maintainability, and production-grade performance across the full development lifecycle.
- Extraction System Development : Develop and optimize AI-driven extraction workflows using techniques such as document parsing, chunking, embeddings, RAG, and LLM-based extraction methods to improve data quality, coverage, and reliability across pipelines.
- Cloud Deployment & Data Pipelines : Deploy and scale AI models on AWS and Azure (SageMaker, Bedrock, Azure AI Foundry), while ensuring seamless integration of AI components with high-throughput upstream and downstream data collection pipelines.
- MLOps & Reliability : Build and maintain CI/CD pipelines for AI model deployment (GitHub Actions, Azure DevOps, Docker, Kubernetes); ensure models are observable and reliable in production using Prometheus and Grafana with defined SLOs and alerting strategies.
- Evaluation & Quality Improvement : Define and implement evaluation frameworks (precision, recall, F1, field-level accuracy); maintain high standards of code quality through design and code reviews, thorough testing, and documentation.
- Collaboration & Stakeholder Alignment : Partner with Product, Data Engineering, and Platform teams to translate business requirements into scalable AI solutions; mentor team members and share knowledge to elevate overall team capability.
- Innovation & Continuous Improvement : Continuously research and apply advancements in NLP, LLMs, and extraction techniques to improve system performance, scalability, and cost efficiency across products.
- Process & Delivery Efficiency : Contribute to efficient development cycles by following Agile practices, continuously improving workflows, and driving automation across the AI delivery pipeline.
Required Skills & Qualifications :
- Bachelor's or master's degree in computer science, Engineering, Data Science, Mathematics, Statistics or related fields.
- At least 3 years of professional experience in AI/ML engineering, with a track record of delivering production-grade AI systems.
- Strong programming skills in Python and SQL, with hands-on proficiency in standard ML/data libraries (scikit-learn, pandas, numpy) and deep learning frameworks (PyTorch or TensorFlow); solid understanding of REST API design and integration patterns.
- Demonstrated hands-on experience building and deploying production-grade ML/LLM systems including RAG pipelines, document parsing, information extraction, and text processing with practical experience handling large-scale unstructured datasets including preprocessing, chunking, and feature engineering.
- Proficiency in cloud-based AI/ML services across AWS and Azure; including AWS SageMaker, Bedrock, and Azure AI Foundry / Azure OpenAI Service; for model training, fine-tuning, deployment, and inference at scale.
- Strong hands-on experience in NLP and extraction-focused ML , including transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows with a solid understanding of how to apply these techniques to real-world production systems.
- Experience leading projects or teams, managing technical deliverables, and ensuring high-quality outcomes; strong analytical and problem-solving capabilities with the ability to navigate ambiguous technical challenges.
- Ability to design and use multi-agentic coding frameworks and orchestration tools (e.g. Claude Code, LangGraph, LangChain, CrewAI) for building and managing LLM-based agentic workflows.
- Solid grounding in Machine Learning and Deep Learning; including supervised/unsupervised learning, CNNs, RNNs, Transformers, NLP, and fine-tuning of pre-trained LLMs for domain-specific tasks; experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement.
- Hands-on experience with MLOps practices; including experiment tracking (MLflow, Weights & Biases), model versioning, automated retraining pipelines, model registry management, and continuous iterative improvement in production.
- Experience with CI/CD pipelines for AI/ML workflows using GitHub Actions, Azure DevOps, or similar; containerization with Docker and orchestration with Kubernetes.
- Proficiency in AI observability and monitoring using Prometheus and Grafana, including setting up dashboards, alerts, and SLOs for production model performance.
- Familiarity with data pipeline and orchestration tools such as Apache Kafka, Apache Airflow, or similar technologies for managing high-throughput data flows.
- Effective communication and collaboration skills, with experience working cross-functionally with product, engineering, and data teams in fast-paced, data-driven environments.
- Relevant certifications are a strong plus including AWS (Solutions Architect, Machine Learning Specialty), Azure (AI Fundamentals, AI Engineer Associate), and Databricks (Machine Learning Professional, Generative AI Engineer Associate).
Why join us?
- Work with a passionate and innovative team in a fast-paced, growth-oriented environment.
- Work on high-impact, real-world AI projects across diverse industries with global clients.
- Collaborate with senior AI architects and domain experts to accelerate your technical depth.
- Contribute to exciting initiatives and make an impact from day one.
- Competitive compensation, fast-track appraisals, and a clear path for growth into senior leadership.
- Recognized for excellence in data and AI solutions with industry awards and accolades.
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