AI/ML Engineer

Must Have Technical/Functional Skills
• Technical Skills

5+ years in data engineering, AI engineering, or knowledge graph development
• Hands-on experience with knowledge graph technologies (property graph and/or RDF frameworks)
• Experience with Cypher and/or SPARQL
• Strong data modeling and ontology design skills
• Experience integrating relational databases and external data sources
• Strong Python development skills
• Experience integrating LLMs into enterprise applications
• Familiarity with RAG architecture and AI-driven recommendation systems

Roles & Responsibilities
• Design and implement knowledge graph architecture using property graph and/or RDF-based models
• Transform and integrate structured and semi-structured data into optimized graph structures
• Develop and query graph systems using Cypher and/or SPARQL
• Design ontologies and entity relationship models to support sales intelligence use cases
• Integrate knowledge graphs with LLMs using Retrieval-Augmented Generation (RAG) architecture
• Build APIs and application services to deliver AI-driven prospecting insights
• Implement scoring, relationship strength analysis, and network traversal logic
• Ensure scalability, security, and enterprise-grade performance
• Partner with sales and business stakeholders to translate requirements into technical solutions

Preferred Qualifications
• Experience building sales intelligence or CRM-adjacent platforms
• Knowledge of embeddings, semantic search, and vector databases
• Experience designing relationship scoring or network analytics models • Cloud platform experience (AWS, Azure, or GCP)
• Experience in financial services or insurance environments.

Success Criteria
• Deliver a scalable knowledge graph + AI solution that enhances sales prospect identification and relationship insights
• Enable measurable improvements in targeting precision and cross-sell opportunity identification
• Establish a reusable architecture pattern for enterprise AI-driven sales initiatives

TCS Employee Benefits Summary:


Discretionary Annual Incentive.


Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.


Family Support: Maternal & Parental Leaves.


Insurance Options: Auto & Home Insurance, Identity Theft Protection.


Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.


Time Off: Vacation, Time Off, Sick Leave & Holidays.


Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $120,000 - $140,000 a year