E T Consultant (senior Genai Engineering Practitioner – SDLC & Agentic AI)

E T Consultant (Senior GenAI Engineering Practitioner – SDLC & Agentic AI)

Do you want to build a career that is truly worthwhile? Working at the World Bank Group provides a unique opportunity for you to help our clients solve their greatest development challenges. The World Bank Group is one of the largest sources of funding and knowledge for developing countries; a unique global partnership of five institutions dedicated to ending extreme poverty, increasing shared prosperity and promoting sustainable development. With 189 member countries and more than 130 offices worldwide, we work with public and private sector partners, investing in groundbreaking projects and using data, research, and technology to develop solutions to the most urgent global challenges.

The Information and Technology Solutions (ITS) Vice Presidential Unit (VPU) enables the World Bank Group to achieve its mission of ending extreme poverty and boost shared prosperity on a livable planet by delivering transformative information and technologies to its staff working in over 150+ locations.

The ITS Finance (ITSFI) unit builds and operates enterprise financial systems supporting WBG business processes. As part of ongoing modernization, the unit is advancing two priorities: improving end-to-end software delivery performance and building an internal agentic AI capability to enhance SDLC knowledge and execution.

The Senior GenAI Engineering Practitioner will work across these two tracks. The role embeds within delivery teams to assess and improve execution across the SDLC, while contributing hands-on to the design and development of an internal agentic AI platform that leverages SDLC artifacts.

The position requires a senior practitioner mindset — combining hands-on engineering, experimentation, and pragmatic implementation. The role operates within an established technology and platform strategy and focuses on measured improvement, not architectural redesign.

Duties and Responsibilities

A. SDLC Assessment and Improvement

• Embed with agile teams to assess current SDLC practices across requirements, development, testing, and release

• Identify gaps in delivery flow, quality, and developer productivity

• Design and execute small-scale experiments using GenAI tools to improve outcomes

• Establish baseline metrics and track measurable improvements over time

• Produce implementable recommendations aligned with the existing tooling ecosystem

B. GenAI Enablement within Engineering Workflows

• Apply modern GenAI tools (e.g., coding assistants, prompt workflows) to real development scenarios

• Develop reusable patterns for prompt engineering, code generation, and test automation

• Partner with teams to incorporate GenAI into daily engineering practices

• Evaluate impact on developer productivity, quality, and cycle time

• Document practices for broader adoption across the portfolio

C. Agentic AI Framework Contribution

• Contribute hands-on to the design and prototyping of an internal agentic AI framework

• Build and evaluate agent workflows leveraging SDLC artifacts (code, backlog, documentation)

• Support integration of agent capabilities into engineering and delivery processes

• Collaborate with a small internal team on experimentation, evaluation, and iteration

• Ensure practical applicability of solutions within enterprise constraints

D. Measurement, Adoption, and Scaling

• Define and track KPIs linked to SDLC efficiency and GenAI adoption

• Translate experimental outcomes into scalable practices

• Support teams in adopting validated improvements

• Provide structured updates on insights, risks, and results

• Balance experimentation with delivery commitments

E. Stakeholder Engagement

• Work closely with engineering teams, product roles, and leadership

• Communicate findings clearly, with evidence and practical implications

• Provide grounded, experience-based perspectives on trade-offs

• Operate effectively within an established strategic direction

Selection Criteria

Education and Experience:

• a Master's degree with 5 years of experience or a Bachelors Degree with a minimum of 7 years of relevant experience, or equivalent combination of education and experience.

Required:

• 5+ years as a software engineering practitioner (Staff/Principal/Engineering Manager level or equivalent)

• Hands-on experience with GenAI tools within the last 24 months, applied to real engineering workflows

• Demonstrated ability to improve SDLC practices through practical implementation

• Experience working within structured delivery environments (e.g., Agile at scale)

• Strong written and verbal communication skills

Preferred:

• Experience with agentic frameworks (e.g., multi-agent workflows, orchestration frameworks)

• Background in financial services or other regulated environments

• Familiarity with SAFe Agile or similar scaled frameworks

Other Competencies:

• Ability to operate independently and drive outcomes

• Strong problem-solving and experimentation mindset

• Pragmatic approach to balancing innovation and delivery

WBG Culture Attributes:

1. Sense of urgency: Anticipate and quickly respond to the needs of internal and external stakeholders.

2. Thoughtful risk-taking: Challenge the status quo and push boundaries to achieve greater impact.

3. Empowerment and accountability: Empower yourself and others to act and hold each other accountable for results.