Senior AI-Driven DevSecOps & SRE Architect

Tata Consultancy Services Limited

Charlotte (NC)

On-site

USD 180,000 - 240,000

Full time

2 days ago

Be an early applicant

A complete application in a minute

Tailored resume and cover letter, ready to send.

Get past ATS filters

Job summary

Tata Consultancy Services Limited is seeking a senior software engineering leader in Charlotte, NC to shape and own the internal AI platform and production engineering strategy. You will blend hands-on coding with mentorship, balancing architectural decisions with delivery, and driving security, reliability, and cost optimization across the stack.

This role emphasizes leading cross-functional teams, defining governance and standards, and partnering with DevSecOps and cognitive engineering

Qualifications

8+ years of software engineering experience, incl. 3+ years in senior/staff roles
2+ years with AI/ML experience
Deep expertise in Python and TypeScript, able to architect full stack
Expert-level AWS – ECS, Lambda, DynamoDB, IAM, VPC, CloudFormation/Terraform
Production experience – incident management, SLOs, capacity planning
CI/CD platform ownership at scale – GitLab CI, environment orchestration
Security engineering background – threat modeling, IAM design, compliance
Experience with AI/ML systems – LLM integration, prompt engineering, embeddings
Mentoring engineers and raising team capabilities
Excellent communication – translate tech decisions for leadership
Independent operation in ambiguous environments
History of driving organizational-level tech improvements
Hands-on coding while mentoring and leading
Ability to switch between strategic and tactical work
Experience with EventBridge, Terraform, GitLab CI, Docker, Dynatrace, Jira/Confluence/ServiceNow APIs, AI Gateway

Responsibilities

Drive decisions for internal AI platform – service design, data modeling, API contracts
Establish engineering standards – code quality, testing, security, deployment patterns
Lead design reviews and technical decision-making for the team
Define and evolve AI governance framework – trust levels, approvals
Represent engineering in cross-functional forums – architecture reviews, security
Own technical roadmap alignment across DevSecOps, RM, and Cognitive Engineering
Own production reliability – SLOs, incident responses, on-call rotation
Design self-healing automation and observability strategy
Manage cost optimization and capacity planning for AWS infra
Lead AI platform direction – governance, model evaluation, knowledge tokens