Analytics and AI Software Engineer

About The Job:

• Join the Analytics & AI Services team to design and deliver enterprise-scale AI and analytics solutions.
• Develop innovative applications leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and intelligent search technologies.
• Support the creation of data-driven products that improve decision-making, knowledge discovery, and business efficiency.
• Collaborate with business stakeholders, data engineers, architects, and AI specialists to translate requirements into scalable solutions.
• Contribute to AI experimentation, solution evaluation, and continuous model improvement initiatives.
• Work on structured and unstructured data to enable conversational insights and intelligent automation.
• Apply research-driven approaches to solve complex business problems and identify innovation opportunities.
• Participate in the development of enterprise AI capabilities aligned with strategic business objectives.
• Ensure solutions comply with data governance, architecture, and security standards.
• Drive adoption of modern AI practices and emerging technologies across the organization.

Essential Job Functions:

• Design and implement Retrieval Augmented Generation (RAG) architectures and semantic search solutions.
• Develop and optimize AI-powered applications using LLMs, reasoning frameworks, and agentic systems.
• Build prototypes and proof-of-concepts using Python and modern AI development tools.
• Create SQL-based analytical solutions using BigQuery, Teradata, or similar enterprise platforms.
• Conduct experimentation, statistical analysis, and model evaluation to assess solution performance.
• Perform literature reviews, research analysis, and hypothesis-driven testing to validate AI approaches.
• Support development of conversational analytics, Dialogue with Data (DwD), and NL2SQL capabilities.
• Collaborate with architecture and product teams to align solutions with enterprise data standards.
• Document technical designs, evaluation results, and implementation best practices.
• Contribute to continuous improvement, innovation programs, and AI capability building initiatives.

Qualifications:
Skill Requirement

• Strong understanding of retrieval methods, search strategies, and enterprise RAG architectures.
• Hands-on experience with LLM architectures, prompt engineering, reasoning techniques, and agentic workflows.
• Advanced SQL proficiency with experience in BigQuery, Teradata, or equivalent databases.
• Strong Python programming skills for AI prototyping, automation, and analytics development.
• Knowledge of evaluation frameworks, A/B testing, experimentation methodologies, and statistical techniques.
• Experience analyzing large datasets and deriving actionable business insights.
• Understanding of semantic layers, metrics modeling, and business semantic frameworks.
• Familiarity with knowledge representation concepts including ontologies and metadata structures.
• Exposure to conversational AI, Text-to-SQL, NL2SQL, and Dialogue with Data solutions.
• Strong analytical, problem-solving, communication, and stakeholder management capabilities.

Other Requirement

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related discipline.
• 12-24 months of relevant experience in AI, analytics, software engineering, or data-focused roles.
• Ability to work effectively in a global offshore delivery model.
• Strong written and verbal communication skills with technical and non-technical audiences.
• Experience working within Agile, Scrum, or iterative software delivery environments.
• Demonstrated ability to manage competing priorities and meet project deadlines.
• Interest in emerging AI technologies, research publications, and industry advancements.
• Understanding of enterprise data governance, security, and compliance principles.
• Ability to work independently while collaborating across multiple teams and stakeholders.
• Commitment to continuous learning, knowledge sharing, and innovation-driven development.

Additional Request 

• Desirable exposure to semantic technologies, taxonomy development, and metadata management practices.
• Basic understanding of knowledge graphs and graph-based reasoning methodologies.
• Familiarity with ontology design and enterprise knowledge management concepts.
• Awareness of LBG data architecture standards and data product management principles.
• Exposure to metrics-driven data products and semantic business models.
• Understanding of conversational analytics patterns and natural language interaction frameworks.
• Interest in applying AI solutions to enhance search, discovery, and knowledge retrieval use cases.
• Ability to evaluate emerging AI tools and recommend suitable enterprise applications.
• Experience contributing to proof-of-concepts, innovation programs, and research initiatives is advantageous.
• Passion for leveraging AI and analytics to deliver measurable business value, improved user experiences, and scalable enterprise solutions.