Senior AI Engineer | Remote | Jobs In India

DigitalXNode; Ahmedabad District; À distance; INR 2 500 000 - 4 200 000; Plein temps

Résumé du poste

DigitalXnode is seeking a Senior AI Engineer in India to build agentic AI pipelines, LLM-powered services, and enterprise semantic models. You will work on knowledge graphs, CIM-aligned ontologies, and modern data engineering workflows, with strong emphasis on Python and Generative AI.

You will implement SPARQL queries, develop Python microservices, and contribute to architecture standards while collaborating with data architects and governance teams to ensure quality, observability, and

Qualifications

• 4–8 years of professional experience with Python and Generative AI.
• Hands-on experience building LLM-based systems.
• Strong understanding of RDF, OWL, ontologies, knowledge graphs, and SPARQL.
• Experience with agentic AI frameworks such as Google ADK, LangChain agents, or similar.
• Strong understanding of data engineering concepts including ETL/ELT, star schemas, and metadata-driven pipelines.
• Experience building and operating systems on cloud platforms, preferably Microsoft Azure and Microsoft Fabric.
• Experience with semantic mapping, ontology enrichment, schema understanding, or related AI/data capabilities.
• Strong problem-solving skills and the ability to work on ambiguous, greenfield platform initiatives.

Responsabilités

• Design, build, and maintain agentic AI pipelines using Google ADK for semantic mapping, dimension mining, and ontology-driven reasoning.
• Create and evolve enterprise ontologies using RDF and OWL, including upper ontologies and domain extensions aligned to CIM where applicable.
• Develop LLM-powered services for schema understanding, semantic alignment, ontology enrichment, and AI-assisted metadata generation.
• Build solutions with a focus on accuracy, traceability, scalability, and consistent semantic interpretation.
• Implement SPARQL querying and reasoning layers over knowledge graphs to support downstream transformations.
• Architect and deliver Python-based microservices and batch pipelines that integrate semantic reasoning with data engineering workflows.
• Develop and improve dimension and fact data pipelines in Microsoft Fabric using Lakehouse, Spark, SQL, and orchestration tools.
• Produce business-ready star schemas from heterogeneous data sources.
• Define engineering standards, design patterns, and reusable components for semantic and AI-driven data platforms.
• Support quality, observability, security, and performance standards across platform components.
• Work with data architects, domain SMEs, and governance teams to validate semantic definitions, manage change, and support platform adoption.
• Conduct code reviews, mentor engineers, and contribute to technical decisions across the platform.

Connaissances

Python

Generative AI

LLM-based systems

RDF/OWL

SPARQL

Google ADK

LangChain

ETL/ELT

Data pipelines

Azure

Microsoft Fabric

Spark

Outils

Google ADK

LangChain

Microsoft Fabric

Spark

Azure

Description du poste

Company Overview

DigitalXnode facilitates clients across industries and continents linking with skilled resources as per their technology and business requirements. We aid in both full-time hiring and staff augmentation by identifying professionals with the right expertise for different projects and engagement models.

Job Summary

We are looking for a Senior AI Engineer with 4–8 years of experience to support our client in India. The role focuses on building agentic AI pipelines, LLM-powered services, enterprise semantic models, knowledge graphs, and modern data engineering workflows. The ideal candidate should have strong proficiency in Python and Generative AI, hands‑on experience with LLM‑based systems, and a solid understanding of RDF, OWL, ontologies, SPARQL, and cloud‑based data platforms.

Key Responsibilities

• Design, build, and maintain agentic AI pipelines using Google ADK or similar frameworks for semantic mapping, dimension mining, and ontology‑driven reasoning.
• Create and evolve enterprise ontologies using RDF and OWL, including upper ontologies and domain extensions aligned to CIM where applicable.
• Develop LLM‑powered services for schema understanding, semantic alignment, ontology enrichment, and AI‑assisted metadata generation.
• Build solutions with a focus on accuracy, traceability, scalability, and consistent semantic interpretation.
• Implement SPARQL querying and reasoning layers over knowledge graphs to support downstream transformations.
• Architect and deliver Python‑based microservices and batch pipelines that integrate semantic reasoning with data engineering workflows.
• Develop and improve dimension and fact data pipelines in Microsoft Fabric using Lakehouse, Spark, SQL, and orchestration tools.
• Produce business‑ready star schemas from heterogeneous data sources.
• Define engineering standards, design patterns, and reusable components for semantic and AI‑driven data platforms.
• Support quality, observability, security, and performance standards across platform components.
• Work with data architects, domain SMEs, and governance teams to validate semantic definitions, manage change, and support platform adoption.
• Conduct code reviews, mentor engineers, and contribute to technical decisions across the platform.

Required Technical Skills

• 4–8 years of professional experience with strong proficiency in Python and Generative AI.
• Hands‑on experience building LLM‑based systems using commercial or open‑source models.
• Strong understanding of RDF, OWL, ontologies, knowledge graphs, and SPARQL.
• Experience with agentic AI frameworks such as Google ADK, LangChain agents, or similar frameworks.
• Strong understanding of data engineering concepts including ETL/ELT, star schemas, and metadata‑driven pipelines.
• Experience building and operating systems on cloud platforms, preferably Microsoft Azure and Microsoft Fabric.
• Experience with semantic mapping, ontology enrichment, schema understanding, or related AI/data capabilities.
• Strong problem‑solving skills and the ability to work on ambiguous, greenfield platform initiatives.

Preferred Skills

• Experience with enterprise data models such as CIM or other canonical models.
• Familiarity with semantic alignment, ontology mapping, or data cataloguing tools.
• Exposure to MLOps, LLMOps, model evaluation, and AI observability.
• Comprehensive experience of distributed systems, CI/CD pipelines, and containerisation.
• Experience building AI‑assisted analytics or semantic layers for BI or NLQ use cases.
• Experience with Retrieval Augmented Generation (RAG) solutions.

AI Experience

AI experience is a core requirement. Candidates should have strong hands‑on experience with Generative AI, LLM‑based systems, agentic AI frameworks, and AI‑assisted semantic or data workflows.

Managerial Experience

Formal people‑management experience is not specified as mandatory. The role includes conducting code reviews, mentoring engineers, and influencing technical decisions across the platform.

Operational Experience

• Experience building and operating cloud‑based AI and data platforms.
• Experience developing production‑oriented microservices and batch pipelines.
• Ability to work with data architects, domain SMEs, and governance teams.
• Experience applying engineering standards around quality, observability, security, and performance.

Qualifications

Any Graduate.

Certifications

No mandatory certification is specified in the source requirements. Relevant AI, cloud, data engineering, or platform certifications may be considered an advantage.

Experience

4–8 years