AI Engineer

Job Description

Design, develop, implement AI and Generative AI solutions to address business problems and achieveobjectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, andoptimizeAI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor andmaintaindeployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploringnew technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams toleveragethese tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering.Code, unit test, debug and perform integration tests of software components Participatein software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizationalobjectivesand high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 6 years of hands-on experience developing AI-based applications using Python. 2+ years in Performance testing, Reliability testing 2+ years of experience using deep learning frameworks (TensorFlow,PyTorch, orKeras) Solid understanding of ML/AI conceptsEDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, theircapabilitiesand limitations. Provenexpertisein integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such asLangchain,Langraph,CrewAIetc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, andmaintainingdata processing systems working in containerized environments (Docker, OpenShift, k8s) Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubefloworsimilar technologies) and exposure to LLMOPs Experience in cost optimisation initiatives Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization,leveragingNLPand integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions toopen sourceprojects