Custom Software Engineer

Project Role : Custom Software Engineer Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs. Must have skills : PySpark Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education

Summary: As a Technology Specialist, you will lead the technical design, development, and deployment of data engineering, machine learning, and knowledge graph solutions. You will manage tech teams, work closely with stakeholders, and build intelligent data platforms and AI-driven applications.

Roles & Responsibilities:

Technical Leadership: Act as a Subject Matter Expert (SME) in Data, ML, and Knowledge Graphs. Lead technical teams, make key architectural decisions, and guide project direction. Data Pipelines: Design and build large-scale data pipelines, enterprise data lakes/lake houses, and real-time streaming platforms. Knowledge Graphs & AI: Build Knowledge Graph solutions, ontologies, and semantic models. Integrate Knowledge Graphs with Large Language Models (LLMs) and Graph RAG applications. ML Deployment: Develop and deploy machine learning models into production using ML Ops best practices. Governance & Operations: Set standards for data governance, metadata management, code quality, and smooth CI/CD (Data Ops/ML Ops) workflows. Mentorship: Guide, mentor, and upskill team members while managing technical project risks.

Professional & Technical Skills:

Strong expertise in PySpark, Apache Spark, and Databricks. Machine Learning experience using Python, TensorFlow, PyTorch, or Scikit-learn. Hands-on experience with Knowledge Graphs and Graph Databases (e.g., AWS Neptune, Neo4j, Stardog) using RDF, OWL, and SPARQL. Experience with Generative AI, LLMs, and GraphRAG integration. Proficiency in SQL, NoSQL databases, and building batch/streaming pipelines. Cloud experience with at least one platform: Azure, AWS, or GCP.

Good to Have:

Microsoft Fabric, Azure Synapse, or Azure ML. Vector databases, LangChain, or Semantic Kernel. MLflow or Kubeflow.

Additional Information: Overall IT Experience: 10+ years. PySpark / Data Engineering: 5+ years. Machine Learning / AI: 3+ years. Knowledge Graphs: 2+ years. Education: 15 years of full-time education. Job Location: Bengaluru, India.

15 years full time education

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