Delivery Manager (AI in SDLC)

EPAM Systems; Malaysia; On-site; MYR 120,000 - 180,000; Full time

Job summary

EPAM Systems in Malaysia is seeking a Delivery Manager focused on AI within the SDLC to lead end-to-end delivery of AI and GenAI initiatives, from discovery to production rollout. You will coach teams to integrate AI into the software delivery lifecycle, align stakeholders, and drive measurable value through governance and risk management.

The role requires hands-on experience delivering ML/GenAI in production, plus deep understanding of the AI lifecycle, MLOps, and CI/CD practices, with the

Qualifications

• Delivery leadership across complex SDLC programs with clear outcome ownership.
• Hands-on experience delivering machine learning and Generative AI solutions into production.
• Understanding of the AI lifecycle including experimentation, evaluation, deployment and monitoring.
• Familiarity with MLOps and CI/CD practices.

Responsibilities

• Own end-to-end delivery of AI and Generative AI initiatives from discovery through production rollout.
• Coach delivery teams on integrating AI into the software delivery lifecycle.
• Align stakeholders through clear governance, risk management and delivery updates.
• Track outcomes using delivery metrics, value realization and adoption measurement.
• Apply Agile and Lean ways of working to build repeatable AI delivery frameworks.
• Embed responsible AI, data privacy and model risk practices across delivery.

Skills

Delivery leadership

AI/GenAI delivery

MLOps

CI/CD

Stakeholder management

Agile/Lean

Job description

We are seeking a Delivery Manager (AI in SDLC) who combines deep SDLC delivery expertise with hands‑on knowledge of AI/GenAI solutions.

Responsibilities

• Own end-to-end delivery of AI and Generative AI initiatives from discovery through production rollout.
• Coach delivery teams on integrating AI into the software delivery lifecycle.
• Align stakeholders through clear governance, risk management and delivery updates.
• Track outcomes using delivery metrics, value realization and adoption measurement.
• Apply Agile and Lean ways of working to build repeatable AI delivery frameworks.
• Embed responsible AI, data privacy and model risk practices across delivery.
• Coordinate distributed, cross‑functional teams to maintain delivery health and predictability.

Requirements

• Delivery leadership across complex software delivery lifecycle programs with clear outcome ownership.
• Hands‑on experience delivering machine learning and Generative AI solutions into production.
• Understanding of the AI lifecycle including experimentation, evaluation, deployment and monitoring.
• Familiarity with MLOps and continuous integration and continuous delivery (CI/CD) practices.
• Ability to turn ambiguity into actionable plans for technical and non‑technical audiences.
• Confidence engaging executive stakeholders on delivery strategy, progress and trade-offs.
• Background leading distributed, multicultural teams across functions.