Enterprise AI Architect

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

• o Static Application Security Testing (SAST) o Software Composition Analysis (SCA) o Container Security Scanning o Dependency Management o Policy Compliance Validation o 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

• o Enterprise Architect Agent o Solution Architect Agent o Data Architect Agent o Backend Engineering Agent o Test Engineering Agent o Security Review Agent o 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

• o Visual Studio Code with GitHub Copilot o Claude Code o OpenAI Codex o 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: o Databricks Lakehouse o Databricks Genie o Delta Lake o ML/AI Pipelines o Snowflake Cortex/CoCo o 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 & amp; Training Reimbursement.

Time Off

Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance

Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-SP1 </div

Qualifications

BACHELOR OF COMPUTER SCIENCE