AI Engineer Job at Renner Brown (Iselin)

Job Description

The Sr Manager is (an expert in AI/ML, GenAI, LLMs, AWS, Java Spring Boot, Python, Node.js, Angular, Microservices, TypeScript, JavaScript, Python, MongoDB, SQL Server, and React Native stack) 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. Develop and implement a systems architecture that will meet business needs. The Sr. Manager's responsibilities include requirements analysis, assessing the current software systems in place to identify areas in need of improvement, and overseeing development teams, including code reviews.

Job Responsibility

Responsible for building innovative software products using various software architecture patterns with solid design principles
Hands-on coding experience and ability to guide younger team members with any issues & help with PR review to deliver the best technical solutions
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, testing
Oversee and maintain cloud infrastructure (e.g., AWS, Azure) specifically for Large Language Model workloads, ensuring cost-efficiency and scalability
Advises software software-related technology standard requirements, methodology, and processes
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 plan design for software projects
Works with enterprise standards to ensure compatibility and integration of multi-vendor platforms
Responsible for impact analysis and design modifications to existing systems to support new solutions
Develops specifications for interfaces from existing to new systems
Maintain a common documentation library of standardized procedures and configurations
Provide third-level support for incidents and problems in designated areas of expertise

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
At least 3 years of experience as an AI engineer within public cloud platforms, AI-driven applications
Proven ability to define and deliver complex technical products involving machine learning, recommendation engines, or analytics
Demonstrated track record of delivering high-quality software products at scale
Strong data analytics skills
9+ years’ experience working in AWS, Java Spring Boot, Node.js, Angular .NET Core, Microservices, TypeScript, JavaScript, Python, MongoDB, SQL Server, and React Native stack
At least three years of experience with architecting using public cloud services, PaaS/SaaS/IaaS on Azure/AWS
Experience with DevOps, CI/CD, and configuration management technologies such as Terraform, Chef/Ansible, Azure DevOps, Azure CLI, and PowerShell
Ability to write software system design documents or review design documents provided by others
Excellent communication and interpersonal skills
Demonstrated ability to thrive in a fast-paced, dynamic environment
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, Llama2, Llama3, 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
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)

Nice to have

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

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