Senior AI Engineer

Allstate India Private Limited; Pune District, Bengaluru; Hybride; INR 350 000 - 700 000; Plein temps

Résumé du poste

Allstate India Private Limited is seeking a seasoned software engineer to design, build, and maintain agentic AI pipelines and enterprise ontologies, aligned to CIM, using RDF/OWL and SPARQL.

You will engineer LLM-powered services, implement knowledge-graph queries over distributed systems on Microsoft Fabric and Azure, and collaborate with data architects to scale semantic platforms across the enterprise.

Qualifications

• 6+ years of professional software engineering experience, with strong proficiency in Python and GenAI.
• Hands-on experience building LLM-based systems using commercial or open-source models.
• Solid understanding of semantic technologies: RDF, OWL, ontologies, knowledge graphs, and SPARQL.
• Experience designing or working with agentic AI frameworks (e.g., Google ADK, LangChain agents, or similar).
• Strong background in data engineering concepts (ETL/ELT, star schemas, metadata-driven pipelines).
• Experience building and operating systems on cloud platforms, preferably Microsoft Azure / Microsoft Fabric.

Responsabilités

• Design, build, and maintain agentic AI pipelines to automate semantic mapping, dimension mining, and ontology-driven reasoning.
• Create and evolve enterprise ontologies in RDF/OWL, including upper ontologies and domain extensions aligned to CIM.
• Engineer LLM-powered services for schema understanding, semantic alignment, ontology enrichment, and AI-assisted metadata generation.
• Implement SPARQL querying and reasoning layers over knowledge graphs to drive downstream transformations.
• Architect and deliver Python-based microservices and batch pipelines that integrate semantic reasoning with data engineering workflows.
• Build and optimize dimension and fact generation pipelines on Microsoft Fabric to produce business-ready star schemas from heterogeneous sources.
• Define and enforce engineering standards, design patterns, and reusable components for semantic and AI-driven data platforms.
• Partner with data architects, domain SMEs, and governance teams to validate semantic definitions and ensure platform scalability.
• Conduct code reviews, mentor engineers, and influence technical decisions to raise quality and velocity.

Connaissances

Python

GenAI

Semantic tech

RDF/OWL

SPARQL

LLM systems

Azure Cloud

Microsoft Fabric

Agentic AI

Data engineering

Outils

Azure Cloud

Microsoft Fabric

Kubernetes

Description du poste

Job Description

Key Responsibilities

• Design, build, and maintain agentic AI pipelines (using Google ADK or similar frameworks) to automate semantic mapping, dimension mining, and ontologydriven reasoning.
• Create and evolve enterprise ontologies in RDF/OWL, including upper ontologies and domain extensions aligned to CIM (where applicable), to enable reusable enterprise semantics.
• Engineer LLMpowered services for schema understanding, semantic alignment, ontology enrichment, and AIassisted metadata generation, with a focus on accuracy, traceability, and scale.
• Implement SPARQL querying and reasoning layers over knowledge graphs to drive downstream transformations and ensure consistent interpretation of business concepts.
• Architect and deliver Pythonbased microservices and batch pipelines that integrate semantic reasoning with modern dataengineering workflows.
• Build and optimize dimension and fact generation pipelines on Microsoft Fabric (Lakehouse, Spark, SQL, orchestration) to produce businessready star schemas from heterogeneous sources.
• Define and enforce engineering standards, design patterns, and reusable components for semantic and AIdriven data platforms (quality, observability, security, and performance).
• Partner with data architects, domain SMEs, and governance teams to validate semantic definitions, manage change, and ensure platform scalability and adoption.
• Conduct code reviews, mentor engineers, and influence technical decisions across the platform to raise engineering quality and delivery velocity.

Required Skills & Qualifications:

• 6+ years of professional software engineering experience, with strong proficiency in Python and GenAI.
• Handson experience building LLMbased systems using commercial or opensource models.
• Solid understanding of semantic technologies: RDF, OWL, ontologies, knowledge graphs, and SPARQL.
• Experience designing or working with agentic AI frameworks (e.g., Google ADK, LangChain agents, or similar).
• Strong background in data engineering concepts (ETL/ELT, star schemas, metadatadriven pipelines).
• Experience building and operating systems on cloud platforms, preferably Microsoft Azure / Microsoft Fabric.
• Strong problemsolving skills and ability to work in ambiguous, greenfield platform initiatives.

Preferred Skills:

• Experience with enterprise data models (e.g., CIM or canonical models).
• Familiarity with semantic alignment, ontology mapping, or data cataloguing tools.
• Exposure to MLOps / LLMOps, model evaluation, and AI observability.
• Knowledge of distributed systems, CI/CD pipelines, and containerisation.
• Experience building AIassisted analytics or semantic layers for BI or NLQ use cases.