Sr Manager, IT Development.Information Tech.IT Development

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.

KEY POSITION REQUIREMENTS

Education

• Bachelor’s or Master’s 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 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.

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, 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
•  

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 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.