AI Architect

Tata Consultancy Services Ltd

  • Minneapolis, MN
  • 7 days ago
  • $130,000–$150,000 Per Year

Highlights

Design and implement AI Engineering Harnesses supporting build validation, quality gates, security scanning, automated testing, and deployment automation. Leverage repository-wide reasoning, large-scale codebase analysis, architecture discovery, code modernization, and AI-assisted implementation patterns.

Numbers & Facts

LocationMinneapolis, MN
Salary$130,000–$150,000 Per Year

Description

Role: Enterprise Architect

Required Skills: Artificial Intelligence | API(Application programming interface)

Qualification: BACHELOR OF COMPUTER SCIENCE

Experience: 10 - 16 Years

Function: TECHNOLOGY

Apply By: 2026-11-27

. 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.

  1. 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.

  1. 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.

  1. 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)

Enterprise AI Architect | Job Description Page 2

  • 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.
  1. 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.

  1. 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.

  1. 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
  • Enterprise Data Governance

Enterprise AI Architect | Job Description Page 3

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

capabilities.

Preferred FDE-Focused Skills

Must-Have

Enterprise Architecture • Solution Architecture • Full Stack Development • AI-Assisted Software Engineering • GitHub

Copilot • Claude Code • Codex • Agentic AI Frameworks • Cloud Architecture (Azure/AWS/GCP) • Modern CI/CD •

DevSecOps • Microservices Architecture • API Design • Platform Engineering • AI Engineering

Security & Compliance

OWASP • HIPAA • PHI/PII Controls • SAST • SCA • Container Security • Zero Trust Architecture • Secure SDLC

Observability & Operations

OpenTelemetry • Distributed Tracing • Monitoring & Alerting • Application Performance Management • Reliability

Engineering • Production Readiness Reviews

Data & AI Platforms

Databricks • Databricks Genie • Snowflake Cortex • Lakehouse Architecture • Data Governance • AI/ML Platforms

Salary Range: $130,000-$150,000 a 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 & amp; Training Reimbursement.

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

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

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