AI SDLC Solutions Consultant — Remote, Drive Adoption

EPAM Systems; San Jose (CA); À distance; USD 160 000 - 220 000; Plein temps

Avantages offerts par ce poste

Medical, Dental and Vision Insurance (

Health Savings Account

Unlimited LinkedIn learning

Résumé du poste

EPAM Systems is seeking an AI SDLC Solutions Consultant to drive AI adoption across the full SDLC within the Engineering Excellence Program. The role requires technical depth, customer-facing skills, and the ability to deliver demos and workshops that demonstrate AI-driven engineering improvements.

Applicants will map AI capabilities to engineering goals, develop proposals, and establish KPIs to quantify impact on delivery speed, quality, and developer productivity.

Qualifications

• Hands-on experience with AI tools like Claude, Codex, GitHub Copilot, Microsoft Copilot, ChatGPT, or similar platforms.

Responsabilités

• Engages in pre-sales activities by identifying client engineering challenges, mapping AI solutions to objectives, and developing proposals highlighting improvements in delivery speed, quality, and developer productivity.
• Conducts demos and proofs-of-concept to showcase AI capabilities and assess technical feasibility and engineering impact for prospective clients.
• Maintains relationships with potential and existing clients, uncovering opportunities for AI integrations across the SDLC to improve engineering efficiency and quality.
• Collaborates with customers to understand engineering goals, challenges, and success metrics to ensure AI solutions address real-world needs and align with priorities.
• Evaluates existing engineering processes to identify AI-driven improvements in development, testing, and deployment, proposing scalable roadmaps.

Connaissances

Client-facing experience

Pre-sales experience

Outils

Claude

Codex

GitHub Copilot

Microsoft Copilot

ChatGPT

Description du poste

EPAM Systems is seeking an AI SDLC Solutions Consultant to drive AI adoption across the full SDLC within the Engineering Excellence Program. The role requires technical depth, customer-facing skills, and the ability to deliver demos and workshops that demonstrate AI-driven engineering improvements.

Applicants will map AI capabilities to engineering goals, develop proposals, and establish KPIs to quantify impact on delivery speed, quality, and developer productivity.