AI Engineer

Hybrid - Bangalore, IN

Professional, Scientific, and Technical Services

About the position

The IBM Automation team is seeking a passionate and talented AI Engineer to push the boundaries of artificial intelligence. You will design, implement, and deploy advanced AI and autonomous agent solutions that enhance our cloud offerings, enabling smarter automation and significantly improving customer productivity. Collaborating closely with cross-functional teams, you will transform complex AI concepts into practical, real-world applications that deliver measurable value.

Responsibilities

• Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives.
• Gather, clean, and prepare large datasets to ensure readiness for AI model training.
• Train, fine-tune, evaluate, and optimize AI 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 and maintain deployed models, ensuring consistent performance and reliability in production environments.
• Stay up to date with the latest AI/ML advancements, exploring new 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 to leverage these 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.
• Participate in software design reviews, code reviews and project planning.
• Write and review documentation and technical blog posts.
• Contribute to department attainment of organizational objectives and high customer satisfaction.

Requirements

• Bachelor's Degree.
• Minimum 4+ years of hands-on experience developing AI-based applications using Python.
• Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras).
• Experience in Pydantic.
• Solid understanding of ML/AI concepts: EDA, 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, their capabilities and limitations.
• Proven expertise in 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 as Langchain, Langraph, CrewAI etc.
• 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).
• Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders.

Nice-to-haves

• Experience in MLOPs frameworks (BentoML, Kubeflow or similar technologies) and exposure to LLMOPs.
• Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs.
• Understanding of security and ethical best practices for data and model development.
• Contributions to open source projects.
• 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, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s).