Sr Manager, IT Development.Information Tech.IT Development

Ansell

About The Position

The Senior AI Engineer is a technical leader with deep expertise in AI/ML, Generative AI, Large Language Models (LLMs), and modern cloud-native application development. This role is responsible for the design, development, maintenance, and support of enterprise-grade software systems and for delivering scalable architectural solutions across Ansell. He/She should demonstrate advanced programming expertise (Java Spring Boot, Python, Node.js, Angular, TypeScript), particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. He/She is responsible for the development, ongoing maintenance, and support of software systems, and for providing technical expertise and architectural solutions in the applications Ansell-wide. He/She will be responsible for applying software development best practices, principles, theories, and concepts for building software products and enterprise solutions. Ability to develop solutions from the ground up by leveraging suitable modern technologies, and/or current reusable artifacts.

Requirements

Bachelor’s or Master’s degree in Computer Science, IT, or related field.
Certified in at least one Cloud or AI-related Certification.
9+ years of experience in New Product Development, and at least 3 years of experience as an AI engineer using LLMs, AI-driven products & agents.
Proven ability to define and deliver complex technical products involving AI/ML, recommendation engines, or analytics.
Demonstrated track record of delivering high-quality software products at scale.
Strong data analytics skills and experience defining and owning translation of data and end-user insights to drive customer value – from defining product success metrics through to analyzing results, optimizing, and building into future-state MVPs
Proficiency in LLMs, AWS, Python, Java Spring Boot, Node.js, Angular, Microservices, TypeScript, JavaScript.
Experience with REST/SOAP APIs, databases (MongoDB, PostgreSQL), Redis
Familiar with containerization, DevOps, and cloud (AWS, Azure)
Experience in Gen AI Technologies: Agentic AI, LLMs (OpenAI, Azure), LangChain, Semantic Kernel
Knowledge of authentication (OAuth2, JWT, SAML) and enterprise-grade security
Excellent communication and interpersonal skills, with the ability to collaborate effectively across diverse teams and stakeholders.
Demonstrated ability to thrive in a fast-paced, dynamic environment, managing multiple priorities and deadlines effectively.
Strong technical understanding of AI/ML, data architecture, and system integration principles.
Experience with principles and best practices in software development, configuration management, and processes, including leading Agile methodology and planning.
Thorough knowledge of various Services in AWS or Azure specific to AI, Gen AI, and LLMs.
Strong knowledge of Generative AI architectures and methods, including chunking, vectorization, context-based retrieval and search, working with Large Language Models such as Claude, OpenAI GPT 4/5, Llama, Mistral, etc.
Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.
Proven experience in MLOps, LLMOps, or related roles, with hands-on experience deploying and managing machine learning and large language model pipelines.
Deep knowledge of Docker frameworks and orchestration concepts (Kubernetes experience is a plus).
Deep knowledge of source code control and configuration management concepts, and experience with Git and Git workflows, is essential.
Ability to operate in a fast-paced, evolving environment and appropriately prioritize tasks, and keep abreast of the latest technology.
Knowledge and understanding of industry trends and new technologies and the ability to apply trends to architectural and technical implementation needs.
Ability to translate algorithmic capabilities into actionable business insights and customer value.
Exceptional communication, documentation, and stakeholder management skills.
Experience with Agile product management tools (e.g., Jira, Confluence).
Experience with RAG (retrieval-augmented generation) and GenAI guardrails
Prompt engineering and LLM safety governance

Nice To Haves

Proactive Ownership – Takes initiative to identify opportunities for platform and algorithm improvement, driving results with accountability and autonomy.
Knowledge of AI ethics and understanding how to apply Trustworthy AI to ensure safe, responsible, and ethical use of AI technology.
Passion for learning and exploring new generative AI technologies and methods.
Analytical & Technical Acumen – Understands data models and AI methods while maintaining focus on usability, scalability, and measurable impact.
Strategic Communication – Articulates complex technical ideas clearly to both technical and commercial audiences.
Innovative Problem Solving – Champions experimentation and creative solutions to expand Guardian’s digital capabilities.
Collaborative Leadership – Works effectively across global, cross-functional teams, fostering trust and alignment.
Agility in a Global Context – Adapts to shifting priorities and diverse cultural and business environments with resilience and flexibility.

Responsibilities

Responsible for building innovative software products using various software architecture patterns with solid design principles.
Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.
Conceptualize, develop products specifically using Large Language Models, including data acquisition, pre-processing, model training/tuning, deployment, and monitoring
Perform truth analysis to assess the accuracy and effectiveness of Large Language Model outputs, comparing them to known, accurate data
Develop target state architectures and validate with the development team.
Collaborate with Product Owner, product development team, and infrastructure team to ensure support of software development and testing.
Implement and manipulate complex algorithms essential for developing and optimizing generative AI models.
Oversee and maintain cloud infrastructure (e.g., AWS, Azure) specifically for Large Language Model workloads, ensuring cost-efficiency and scalability.
Implement RAG architectures to enhance response relevance using external knowledge sources
Integrate Large Language Models into chatbot workflows for summarization, classification, and intelligent routing, and Agentic AI Agents
Design prompt chaining and semantic search flows for document-based and FAQ based virtual assistants
Design and implement knowledge-based search using AI-driven techniques (e.g., FAQ ingestion, document indexing)
Drive performance optimization, CI/CD integration and code quality standards.
Establish robust monitoring and alerting systems to track Large Language Model performance, data drift, and other key metrics, proactively identifying and resolving issues.
Participates in proof of concepts to assist in technology direction and enabling business strategy.
Conducts and assists in end-to-end technical design for software products.
Responsible for impact analysis and design modifications to existing systems to support new solutions.