Enterprise AI Architect

Tata Consultancy Services; Eden Prairie (MN); On-site; USD 180,000 - 200,000; Full time

Benefits offered by this job

Discretionary annual incentive

Medical coverage

Parental leaves

401K plan

Job summary

Tata Consultancy Services is seeking an Enterprise AI Architect to lead architecture and hands-on development of AI-enabled platforms in a cloud-native, secure environment.

You will define reference architectures, guardrails, and standards, while driving AI-driven software delivery and modernization across the enterprise. Strong focus on observability, governance, and security. Flexible location in the US.

Qualifications

• Bachelor's degree in computer science or related field.
• Extensive hands-on experience with AI engineering and full-stack development.
• Experience with enterprise data platforms and cloud-native architectures.

Responsibilities

• Lead enterprise AI architecture and solution design for large-scale deployments.
• Define reference architectures, standards, and guardrails for scalable AI solutions.
• Drive adoption of agent-based AI, AI-powered development, and intelligent automation.

Skills

Enterprise AI Architecture

Full Development Experience

AI engineering

DevSecOps

Cloud-native technologies

Education

Bachelor of Computer Science

Tools

GitHub Copilot

Claude Code

Codex

Databricks Genie

Snowflake Cortex

Job description

Job Description

Must Have Technical/Functional Skills

Enterprise AI Architect with Full Development Experience (FDE), possessing deep expertise in architecture, hands-on software engineering, AI-assisted development, Agentic AI frameworks, DevSecOps, platform engineering, cloud-native solutions, and enterprise data platforms. Proven ability to architect, develop, secure, automate, and operationalize large-scale AI and software solutions while driving engineering excellence through GitHub Copilot, Claude Code, Codex, Databricks Genie, Snowflake Cortex, and modern AI-powered software delivery practices.

Key Responsibilities

• Enterprise AI & Solution Architecture
• Lead the architecture, design, and implementation of enterprise-scale AI solutions using modern architectural patterns, clean architecture principles, domain-driven design (DDD), and cloud-native technologies.
• Define enterprise AI reference architectures, engineering standards, development frameworks, and implementation guardrails to ensure scalability, maintainability, security, and operational excellence.
• Drive adoption of Agentic AI, AI-powered software engineering, and intelligent automation across the software delivery lifecycle.
• Architect solutions with built-in observability, resilience, governance, security, and compliance from inception through production deployment.
• Partner with business, engineering, security, and platform teams to align AI capabilities with enterprise technology strategy and business outcomes.
• Full Development Experience (FDE) and Engineering Excellence
• Demonstrate hands-on full-stack development experience spanning frontend, backend, APIs, data platforms, cloud services, and AI-enabled applications.
• Lead development teams in implementing modern engineering practices including test-driven development (TDD), CI/CD automation, code quality enforcement, and platform engineering standards.
• Define and enforce software engineering best practices with mandatory automated test coverage, code reviews, architecture reviews, and deployment quality controls.
• Drive modernization of legacy applications through refactoring, cloud migration, microservices transformation, and AI-assisted development methodologies.
• Establish engineering productivity frameworks leveraging AI coding assistants, automated development workflows, and intelligent code generation.
• Secure-by-Design AI Platforms
• Architect secure AI and software platforms aligned with OWASP standards, Zero Trust principles, and enterprise cybersecurity requirements.
• Implement enterprise controls for HIPAA, PHI, PII, GDPR, and regulatory compliance across data, applications, and AI workloads.
• Integrate security validation throughout the development lifecycle using SAST, SCA, container scanning, secrets management, and policy-as-code frameworks.
• Design auditable AI systems with governance, lineage, traceability, access controls, and compliance monitoring capabilities.
• AI Engineering, DevSecOps, and Delivery Automation
• Design and implement AI Engineering Harnesses supporting build validation, quality gates, security scanning, automated testing, and deployment automation.
• Establish enterprise DevSecOps frameworks integrating:
• Static Application Security Testing (SAST)
• Software Composition Analysis (SCA)
• Container Security Scanning
• Dependency Management
• Policy Compliance Validation
• Infrastructure-as-Code Governance
• Lead implementation of performance benchmarking frameworks for APIs, AI models, applications, and distributed platforms.
• Build highly automated CI/CD pipelines enabling secure, reliable, and repeatable software delivery.
• Agentic AI Development Frameworks
• Design and operationalize multi-agent software engineering ecosystems to accelerate architecture, development, testing, security review, and governance activities.
• Utilize specialized AI agents including:
• Enterprise Architect Agent
• Solution Architect Agent
• Data Architect Agent
• Backend Engineering Agent
• Test Engineering Agent
• Security Review Agent
• Pull Request Review Agent
• Drive adoption of agent-based development workflows to improve engineering productivity, software quality, and delivery velocity.
• AI-Assisted Software Engineering Toolchain
• Extensive hands-on experience using:
• Visual Studio Code with GitHub Copilot
• Claude Code
• OpenAI Codex
• Enterprise AI coding assistants
• Leverage repository-wide reasoning, large-scale codebase analysis, architecture discovery, code modernization, and AI-assisted implementation patterns.
• Architect AI-powered developer experiences integrating intelligent code review, automated remediation, documentation generation, and engineering workflow automation.
• Data & AI Platform Architecture
• Design and implement scalable data and AI platforms leveraging Databricks, Snowflake, cloud-native services, and modern data architectures.
• Experience with:
• Databricks Lakehouse
• Databricks Genie
• Delta Lake
• ML/AI Pipelines
• Snowflake Cortex/CoCo

Enterprise Data Governance

• Enable self-service analytics, conversational AI, semantic data access, and enterprise-scale data engineering capabilities.

Salary Range: $180,000 -$200,000 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