Principal Software Engineer - AI in SDLC Tech Lead

GHX

About The Position

GHX is seeking an experienced Principal Engineer with deep technical expertise and a proven track record in operationalizing AI in SDLC. The role reports to the VP of Enterprise Architecture (EA) and will be responsible for discovering/driving how will be used across SDLC aspects including Project Management, Coding, Quality, Security, CICD/IaC, Infrastructure, Incident Management and Operations. The role requires hands-on experience with modern development of languages, tools and technologies. The ideal candidate will be skilled in AWS, Github, Java/Python, LLMs, MCP Servers, Agents, Jira, Confluence.

Requirements

10 years of experience in architecting, designing and developing enterprise-grade software systems.
10 years of experience designing and implementing technological solutions using Java and/or Python languages within cloud environments.
Experienced with AI in SDLC techniques/technologies/tools including AI Enabled IDEs, using AI for Code Explaining/Reviews, using AI for Design/Concept to Code, using AI for Unit-Testing/Code-Coverage/API-Testing, using AI in CICD/IaC, using AI for Code-Refactoring/Version-Upkeep and using AI for Observability/Incident-Management.
Comfortable with Frontend architectures/technologies such as Modular SPA, MFE, BFF, Responsive/Reactive, I18N/L10N.
Comfortable with Backend architectures/technologies such as Sync/Async/Batch Microservices, Chasis, DDD, DTO/DAO, ORM, CQRS, Data Replication, Messaging/Eventing, Orchestration/Workflow , API Styles, API Management/Gateway, Traceability, CircuitBreaker, Feature Switches.
Comfortable with Quality Engineering aspects such as Unit Testing, Code Coverage, API Testing, Performance, Scalability and Resilience aspects/techniques including Tenancy aspects/techniques aspects such as Single-Deployment/Multi-tenant.
Comfortable with Security aspects/techniques/technologies such as DAST, SAST, IAM/AuthN, RBAC/AuthZ, API/Endpoint Security, Secrets Management, Encryption, Logging Aggregation.
Comfortable with DevOps/Infra aspects/techniques such as Cloud Hosting, CICD, IaC, Containers/Clusters, Serverless, Load Balancing, Observability, HA (High Availability), DR (Disaster Recovery) and SLAs.
Comfortable with Data Governance aspects/techniques/technologies such as Classification, Licensing, Rights, Privacy, Sovereignty, Retention/DLM/ILM, Data Quality, Data Standards, Obfuscation, Catalog, Metadata.
Experienced working within Agile SDLC environments.
Able to work independently and as part of a team on multiple overlapping projects and manifest organization skills in order to effectively context-switch as needed.
Strong problem-solving and communication skills.

Nice To Haves

Proven track record of working across multiple projects/workstreams and delivering high-quality results with innovation and creativity.
Communicates complex technical concepts effectively to diverse audiences, including technical and non-technical teams.
Collaborates seamlessly across departments with varying levels of technical expertise.
Demonstrates a strong understanding of system-wide impacts and interdependencies across products, teams, and the organization.
Develops and implements innovative solutions that challenge the status quo and drive process improvement.

Responsibilities

Coordinate/Vet/POC/Choose/Evangelize AI in SDLC Trends, Technologies and Frameworks as well as establishing informed views on what is working/not-working.
Discover, bring awareness to and build knowledge of leading AI in SDLC solution providers including AWS, Azure, Github and Anthropic.
AI in SDLC Partner/Vendor Management.
Define Baseline/Standard AI in SDLC “stack”.
Define Baseline/Standard metrics which measure AI in SDLC effectiveness.
Project Manage the overall AI in SDLC initiative.
Lead and coordinate as an Individual Contributor across Enterprise Teams/Business Units.
Collaborate with cross-functional stakeholders such as Enterprise Architecture, Product Owners, Security, DevOps and Infrastructure Leaders to understand their AI in SDLC requirements/concerns.
Produce, present and evangelize clearly articulated documentation in the form of Approach Presentations, POC Outcomes, Usage Statistics, Wiki Content and Backlogs.
Establish practical, actionable and production-grade guideline content and use it to guide teams in best practices for AI in SDLC as well as mentoring team members and fostering a collaborative environment.
Learn and understand GHX vertical domain level business and functional aspects in order to appropriately shape AI in SDLC approaches/solutions.
Build and maintain strong business relationships to influence decision-making and drive innovative solutions across teams.