- 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.
KEY POSITION REQUIREMENTS
Education- Bachelors or Masters degree in Computer Science, IT, or related field.
- Certified in at least one Cloud or AI-related Certification.
Job Experience- 9+ years of experience in New Product Development, and 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 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
- 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 designing and delivering enterprise-scale solutions.
- 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, 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.
Knowledge and Skills- 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, 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).
DESIRABLE JOB COMPETENCIES- 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 Guardians 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.
ADDITIONAL REQUIREMENTS- Occasional global travel (up to 20%) for workshops, customer engagement, and cross-regional coordination.
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