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# DevSecOps and SRE

- **Company:** Siri InfoSolutions Inc
- **Location:** Charlotte, NC, United States
- **Experience:** Experienced
- **Salary:** $104,000.0 - $114,400.0
- **Contract:** Temporary to permanent
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Confluence, JIRA, Software Quality, Continuous Integration, Software Debugging, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Key Management, Network Segmentation, Open Source Technology, Service Design, Software Engineering, TypeScript, Software Vulnerability Management, Data Logging, ReactJS, Large Language Models, Prompt Engineering, Model Validation, Caching, Amazon Virtual Private Cloud (VPC), AWS ECS, Cloudformation, Fastapi, Servicebus, AI Platforms, Gitlab-ci, Infrastructure Automation Frameworks, Performance Monitor, Machine Learning Operations, Functional Programming, Software Coding, Terraform, GPT, Dynatrace, Devsecops, Api Management, Docker, Servicenow
- **Published:** August 21, 2026
- **Apply:** https://www.careerjet.com/jobad/usd0897a4060bdaf8ccfbbbf9d8a2f0cfe

## About the Role

8+ years of software engineering experience, including 3+ years in senior/staff roles and 2+ years
with AI/ML experience
Deep expertise in Python and TypeScript - able to architect and build across the full stack
Expert-level AWS - ECS, Lambda, DynamoDB, IAM, VPC, CloudFormation/Terraform, multi-account strategies
Production experience - incident management, SLOs, error budgets, capacity planning
CI/CD platform ownership at scale - GitLab CI, pipeline-as-code, environment orchestration
Security engineering background - threat modeling, IAM design, vulnerability management, compliance (FRB, SOX/FFIEC)
Experience with AI/ML systems - LLM integration, prompt engineering, RAG architectures, embedding models
Track record of mentoring engineers and raising team capabilities
Excellent communication - can translate technical decisions for leadership and collaborate across teams
Experience in financial services or similarly regulated environment preferred Must Have (Elevate-specific),
Demonstrated ability to operate independently with minimal direction
History of driving organizational-level technical improvements
Comfort with ambiguity - define the problem, not just solve it
Player-coach mindset - hands-on coding while mentoring and leading
Ability to context-switch between strategic (architecture, roadmap) and tactical (debugging, shipping)
Tech Stack, Python 3.12 | FastAPI | React 19 | TypeScript | AWS (ECS, Lambda, DynamoDB,
EventBridge, IAM, VPC) | Terraform | GitLab CI | Docker | Dynatrace (DQL) | Jira/Confluence/ServiceNow APIs | AI Gateway (GPT/Claude/open-source LLMs)

## Description

Technical Leadership & Application Architecture (30%) - Drive decisions & resolve challenges for internal
AI platform - service design, data modeling, API contracts, scaling strategy, intelligence build - Establish
and enforce engineering standards - code quality, testing practices, security controls, deployment patterns
Lead design reviews and technical decision-making for the team - Define and evolve the team's AI governance
framework - trust levels, approval chains, model evaluation criteria - Represent engineering in cross-functional
forums - architecture review boards, security assessments, compliance audits - Own technical roadmap
alignment between DevSecOps, RM, and Cognitive Engineering workstreams
Production Engineering & SRE (25%) - Own production reliability - SLO definition, error budgets, availability t
argets - Lead complex incident response - triage, cross-team coordination, executive communication Design
and implement self-healing automation - detection, decision, approval, remediation pipelines - Architect
observability strategy - Dynatrace/internal logging instrumentations, alerting, dashboards, DQL
queries - Manage on-call rotation; mentor team on debugging production issues - Drive toil reduction -
identify repetitive operational work, automate or eliminate
DevSecOps & Security (20%) - Own CI/CD platform architecture - pipeline optimization, caching, parallel
execut ion, security gates - Design and implement security controls - IAM policies, network segmentation,
secrets management, vulnerability remediation - Lead infrastructure-as-code practices - Terraform module
design, drift detection, compliance validation - Manage AWS infrastructure at scale - ECS clusters,
Lambda@Edge, DynamoDB capacity planning, cost optimization - Drive container security - image hardening,
ECR scanning, runtime protection
AI & Cognitive Engineering (25%) - Lead internal AI platform technical direction - self-heal engine, knowledge
core, proactive monitoring, COG grid - Design AI pipeline architecture - LLM routing, prompt management,
token budgets, model evaluation - Build the team's AI engineering capabilities - Realted evolving tools
enablement, Guild Commons governance - Own the Ally AI Gateway integration - model selection, fallback
strategies, cost optimization - Pioneer AGI-readiness patterns - multi-model orchestration, approval chains,
confidence-gated autonomy - Drive adoption strategy - enable other teams to contribute personas and
extend the platform


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