Knowledge Engineer

We Love AI Jobs; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Accenture Federal Services in Bengaluru seeks an experienced Knowledge Engineer to design and implement enterprise knowledge graphs, semantic layers, and AI knowledge solutions on AWS. You will lead major workstreams, build data pipelines, and establish LLM grounding capabilities while advising clients and teams on practical adoption of knowledge graphs.

The role requires 12+ years of experience and a Bachelor's degree or equivalent.

Qualifications

• Extensive data engineering experience and knowledge graphs/semantic modeling.
• Hands-on AWS experience including Neptune, S3, Glue and analytics services.
• Proficiency with RDF, SPARQL, and ontology management.
• Strong experience in KB/KG curation and schema design.
• Minimum 12 years of relevant industry experience.

Responsibilities

• Design and build AWS-based knowledge engineering solutions and pipelines.
• Lead ontology, schema, and knowledge graph modeling for enterprise-scale projects.
• Guide engineers and stakeholders on delivery and business value.
• Develop LLM grounding layers, RAG pipelines, and semantic data products.
• Collaborate with cross-functional teams to enable scalable AI knowledge solutions.

Skills

Data engineering

Knowledge graphs

Semantic modeling

AWS

Python

RDF and SPARQL

LLM grounding

Ontology design

Education

Bachelor's degree or equivalent

15 years full time education

Tools

Amazon Neptune

S3

Glue

Lambda

EMR

Redshift

Athena

OpenSearch

Bedrock

SageMaker

IAM

Step Functions

APIs

Job description

# Knowledge EngineerAccenture Federal ServicesBengaluruFull-timeAI tools:BedrockSageMakerTensorFlowPyTorchUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThis senior knowledge engineering role builds enterprise knowledge graphs, semantic layers, and AI knowledge solutions on AWS. You will lead a substantial workstream, develop data pipelines and LLM grounding capabilities, and advise clients and teams on practical knowledge graph adoption.* Full-time* 12+ years* Bachelor's Degree or equivalent### Skills and expertiseData engineeringKnowledge graphs and semantic modelingAWSAmazon NeptunePythonRDF and SPARQLLLM grounding and RAGOntology and schema design### Key responsibilities* Build AWS-based knowledge graph solutions, data pipelines, semantic layers, and LLM grounding capabilities.* Lead ontology, schema, graph modeling, and knowledge curation design for enterprise solutions.* Guide engineers and advise stakeholders on delivery, technical choices, and business value.## How this job comparesCompared with 269 open senior data jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 269 open senior data jobs at 124 companies.Remote work: This job is on site. 60 of the 269 senior data jobs (22%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role builds AI knowledge solutions and LLM grounding layers, including RAG pipelines, vector retrieval, and graph-based ML models.## Full descriptionProject Role : Knowledge EngineerProject Role Description : Design and structure knowledge frameworks that enable AI systems to reason and make informed decisions. Capture and translate expert and unstructured knowledge into ontologies, knowledge graphs, and semantic models, ensuring accuracy and context for automation and insights. Apply advanced analytics on knowledge graphs to drive problem-solving and actionable insights.Must have skills : Data EngineeringGood to have skills : Amazon Web Services (AWS)Minimum 12 year(s) of experience is requiredEducational Qualification : 15 years full time educationRole Summary / DescriptionAI Powered Tech TalentSenior Engineer role in Knowledge Engineering focused on designing, building, and leading significant workstreams for enterprise-scale Knowledge Graph, semantic layer, ontology, and AI knowledge solutions on Amazon Web Services (AWS). The role leads a substantial knowledge engineering scope within a large program, translates real-world business problems into scalable AI and KG solutions, guides technical direction, and contributes to thought leadership, reusable assets, and delivery standards. The role must bring relevant industry experience across domains such as BFSI, healthcare, retail, telecom, manufacturing, energy, public sector, or life sciences, applying semantic AI, knowledge graphs, LLM grounding, data pipelines, and cloud-native engineering patterns to deliver measurable client value.Key ResponsibilitiesEngineer AWS-based knowledge engineering solutions using services such as Amazon Neptune, S3, Glue, Lambda, EMR, Redshift, Athena, OpenSearch, Bedrock, SageMaker, IAM, Step Functions, APIs, and monitoring/security services.Build graph ingestion pipelines, semantic data products, vector integrations, LLM grounding layers, APIs, and governed access patterns on AWS while improving performance, reliability, scalability, and cost efficiency.Lead the build of Knowledge Graph solutions that transform client data architecture within a large program scope.Direct the design, development, and implementation of AI, semantic layer, ontology, taxonomy, schema, graph modeling, and knowledge curation solutions, ensuring all components work together seamlessly.Work with project leaders, delivery leads, client stakeholders, architects, data engineers, AI engineers, product teams, and domain SMEs to create standout graph-powered data and AI offerings.Develop strong client relationships, earn trust as a key advisor, and explain the business value of semantic layer, ontology, and knowledge graph solutions.Make the business case for the recommended semantic layer solution and contribute meaningfully to sales, pre-sales, estimation, proposal inputs, and solution shaping activities.Provide thought leadership on technology trends, innovation opportunities, limitations, risks, delivery concerns, and practical adoption of knowledge graphs, semantic AI, LLM grounding, RAG, and agentic systems.Design, evaluate, and maintain ontologies, schemas, standards, and reusable engineering patterns, while guiding teams on data model quality and implementation methods.Lead a team or workstream within a larger program, mentor engineers, review design/code/configuration, and guide adoption of new methodologies, model building techniques, and algorithms.Collaborate across business and technical teams to drive end-to-end delivery for the assigned scope and demonstrate value to business and technology stakeholders.Required QualificationsBachelor's degree or equivalent in Computer Science, Information Technology, Engineering, Mathematics, Data Science, or a related field.Minimum 3 years of experience with Knowledge Graph technologies such as RDF, SPARQL, LPG, SHACL, OWL, graph query languages, schema design, ontology management, and KG curation.Minimum 3 years of experience in schema design, ontology management, semantic modeling, taxonomy management, metadata management, and knowledge graph curation.