Lead Applied AI Engineer

Tata Consultancy Services; New York (NY); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Discretionary Annual Incentive.

Comprehensive Medical Coverage:Medical

Dental & Vision Coverage

Disability Planning & Insurance

Pet Insurance Plans

Maternal & Parental Leaves.

Auto & Home Insurance

Identity Theft Protection

Commuter Benefits

Certification & Training Reimbursement

Vacation Time Off & Holidays

Job summary

Tata Consultancy Services in New York, NY, seeks a Lead Applied AI Engineer to architect and deliver production-grade AI systems that integrate Generative AI capabilities, AI agents, and modern enterprise platforms. You will define technical standards, mentor engineering teams, and drive enterprise AI adoption.

You will design scalable AI data and retrieval architectures, ensure governance and responsible AI practices, and oversee end-to-end deployment with observability and incident response.

Qualifications

• Bachelor of Computer Science is required.

Responsibilities

• Architect comprehensive end-to-end AI systems including Retrieval-Augmented Generation pipelines, multi-stage retrieval and re-ranking architectures, and agent orchestration frameworks.
• Define enterprise standards for prompt engineering, templates, versioning, testing, and evaluation frameworks.
• Lead deployment of AI solutions into production with observability, logging, reliability practices, and real-time monitoring.

Education

Bachelor of Computer Science

Job description

Job Description

We are seeking an accomplished Lead Applied AI Engineer to architect and deliver advanced AI systems that seamlessly integrate Generative AI capabilities, AI agents, and modern enterprise platforms. This role is responsible for designing, building, deploying, and scaling production‑grade AI solutions that support large‑scale business operations while maintaining high standards of security, reliability, governance, and responsible AI practices. The Lead Applied AI Engineer will define technical standards, lead enterprise AI adoption, establish engineering best practices, and mentor engineering teams. This position operates at the intersection of AI innovation, enterprise architecture, platform engineering, and responsible AI governance.

Key Responsibilities

AI Solution Architecture

• Architect comprehensive end-to-end AI systems including:
  • Advanced RAG (Retrieval-Augmented Generation) pipelines
  • Multi-stage retrieval and re‑ranking architectures
  • Agent orchestration frameworks coordinating multiple specialized agents
  • Multi‑model AI integrations leveraging model‑specific strengths
  • Design solutions with modularity, extensibility, scalability, and operational excellence to support evolving business requirements.

AI Engineering Standards & Optimization

• Define enterprise standards for:
  • Prompt engineering
  • Prompt templates and versioning
  • Testing methodologies
  • Evaluation frameworks
• Establish performance optimization strategies covering:
  • Model selection criteria
  • Caching patterns
  • Resource utilization
  • Cost optimization

Production Deployment & Reliability

• Lead deployment of AI solutions into production environments with:
  • Comprehensive observability
  • Logging and tracing
  • Reliability engineering practices
  • Graceful degradation mechanisms
  • Circuit breaker implementation
  • Real‑time monitoring dashboards
  • Automated alerting
  • Incident response procedures
  • Ensure AI services meet stringent service‑level objectives and enterprise reliability expectations.

Data & Retrieval Architecture

• Design scalable data ingestion frameworks that process:
  • Structured data sources
  • Unstructured documents
  • Real‑time event streams
• Develop:
  • Vector database architectures
  • Hybrid search capabilities
  • Data preprocessing pipelines
  • Data quality monitoring frameworks
• Ensure high‑quality inputs for AI systems through cleansing, enrichment, and governance processes.

AI Evaluation & Continuous Improvement

• Establish quantitative evaluation frameworks for AI systems.
• Implement:
  • A/B testing capabilities
  • Performance benchmarking
  • User feedback analysis
  • Telemetry‑based optimization
• Drive continuous improvements across:
  • Prompts
  • Retrieval strategies
  • Agent workflows
  • Model configurations

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

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.

Qualifications

BACHELOR OF COMPUTER SCIENCE