Knowledge Engineer

Hackajob; Kolkata District, Chennai, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Hackajob is seeking a Knowledge Engineer to lead a large AI and Knowledge Graph program, shaping scalable semantic solutions and data architectures. You will direct KG development, ontology management, and end-to-end data pipelines for AI applications in a multi-cloud environment.

You will collaborate across engineering, research, and product teams across multiple time zones, mentor junior members, and contribute to client engagements with a strong emphasis on thought leadership and strategic

Qualifications

• Bachelor's degree or equivalent required; PhD preferred.
• Minimum 3+ years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).
• Experience in schema design, ontology management, and KG curation.
• Design and development of KG solutions and graph-based ML models (functional + technical).
• 2+ years of hands-on experience with cloud platforms (AWS, Azure, GCP).
• Strong knowledge of relational databases, object stores, graph databases and vector databases.

Responsibilities

• Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope.
• Directs the design, development, and implementation of AI and semantic solutions.
• Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings.
• Develops strong client relationships and earns the trust of key advisors.
• Makes the business case for the semantic layer solution recommended to the client.
• Contributes meaningfully to Accenture sales and pre-sales efforts.
• Provides thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.
• Lead the development and refinement of knowledge representation models to enhance AI capabilities.

Skills

Microsoft Azure Data Services

Machine Learning

Ontology design

Knowledge Graphs

Python

Team leadership

TensorFlow

PyTorch

Education

Bachelor's degree or equivalent

Ph.D. in Computer Science or related field

Tools

TensorFlow

PyTorch

Job description

Summary:

AI Powered Tech Talent

You lead a significant knowledge engineering scope and function within a large program actively contribute to thought leadership. You shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, and set the technical direction for that scope. You lead a team and guide exploration and implementation of new methodologies, model building techniques, and cutting-edge algorithms. You remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. You publish or present perspective beyond the immediate project. You work across business and technical teams to drive end-to-end delivery for their scope.

• Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope.
• Directs the design, development, and implementation of AI and semantic solutions, ensuring all the pieces work together seamlessly.
• Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings.
• Develops strong client relationships and earns the trust of key advisors.
• Makes the business case for the semantic layer solution recommended to the client.
• Contributes meaningfully to Accenture sales and pre-sales efforts.
• Provides thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.
• Bachelor's degree or equivalent
• Bachelor's degree or equivalent, plus at least 4 of the following:
• Minimum 3 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
• Minimum 3 years of experience in schema design, ontology management, and KG curation
• Minimum 3 years of designing and developing KG solutions and graph-based ML models (functional + technical)
• Minimum 2 years of experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration
• Minimum 4 years of experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases
• Minimum 2 years of experience in leading a team or workstream within a larger program
• 2+ years of hands-on experience with cloud platforms (AWS, Azure, GCP)
• 2+ years of experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)
• Practical experience with NLP and/or Search techniques
• Prompt engineering, and LLMs for enterprise-scale applications.
• You have team lead experience
• Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.
• You have external client-facing consulting experience
• Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

Broad experience in diverse ML techniques and agentic systems.

As a Knowledge Engineer, a typical day involves designing and structuring comprehensive knowledge frameworks that empower artificial intelligence systems to reason effectively and make well-informed decisions. This role requires capturing expert knowledge and transforming unstructured information into organized ontologies, knowledge graphs, and semantic models. Throughout the day, the Knowledge Engineer ensures that these frameworks maintain accuracy and contextual relevance, supporting automation and generating valuable insights. Additionally, the role includes applying advanced analytical techniques to knowledge graphs to facilitate problem-solving and derive actionable intelligence that benefits various organizational functions.

Roles & Responsibilities:

• Expected to be an SME, collaborate and manage the team to perform.
• Responsible for team decisions.
• Engage with multiple teams and contribute on key decisions.
• Provide solutions to problems for their immediate team and across multiple teams.
• Lead the development and refinement of knowledge representation models to enhance AI capabilities.
• Facilitate knowledge sharing and communication between cross-functional teams to ensure alignment and integration.
• Mentor junior team members by providing guidance and support to foster professional growth.
• Continuously evaluate emerging technologies and methodologies to improve knowledge engineering processes.

Professional & Technical Skills:

• Must To Have Skills: Proficiency in Microsoft Azure Data Services.
• Good To Have Skills: Experience with Machine Learning (ML).
• Strong expertise in designing and implementing ontologies and semantic models.
• Experience in building and managing knowledge graphs for complex data relationships.
• Ability to apply advanced analytics techniques to extract insights from structured and unstructured data.
• Familiarity with data integration and transformation processes within cloud environments.

Additional Information:

• The candidate should have minimum 7.5 years of experience in Microsoft Azure Data Services.