SDLC AI:
We are seeking a highly skilled Software Engineer with
recent Vibe coding experience to lead the design and implementation
of intelligent solutions across the Software Development Life Cycle (SDLC),
specifically leveraging the GitHub ecosystem. This role is focused on
architecting and integrating sophisticated AI-driven workflows,
including specialized coding agents, custom agents, and comprehensive Skills
libraries, while ensuring all solutions adhere to rigorous engineering
standards.
Key Responsibilities:
- AI
Agent Engineering & Tuning: Architect and maintain advanced
AI agents for coding and automation within GitHub workflows. This
includes the active building, performance tuning, and refinement of
agentic logic to ensure optimal performance.
- Evaluation
& Quality Assurance: Implement robust evaluation
frameworks to ensure that all AI-driven solutions meet
established technical standards and best practices before
deployment.
- Standardisation
(Prompt Ops): Develop and govern prompt libraries,
instruction sets, and organizational standards to ensure consistency and
reliability in AI usage across all engineering teams.
- System
Orchestration: Integrate AI solutions seamlessly with CI/CD
pipelines and Model Context Protocol (MCP) servers to
create automated, end-to-end development cycles.
- Strategic
Collaboration: Partner with cross-functional engineering teams to
embed AI-driven processes directly into core SDLC
methodologies.
Technical Requirements:
- Programming
Proficiency: Advanced expertise in Python or TypeScript.
Professional experience with Rust, Golang, or Java is highly
desirable.
- Ecosystem
Expertise: Deep knowledge of the GitHub stack, Claude Code or
Codex, including hands-on experience with CI/CD integration and
complex automation tools.
- Architectural
Insight: A comprehensive understanding of AI frameworks and agent-based architectures, moving beyond simple prompts to
multi-step agentic workflows.
- Engineering
Standards: The ability to write clear, reusable prompts and
Skills while maintaining the highest coding standards and
documentation.
· Note:
· have the candidates operated in large scale
enterprise/industrial SDLC (large enterprises with complex process/tools).
Given they need to apply their genAI skills in the context of a transformation
from old to new…leading/guiding/designing how old style meets new style of
engineering. Often we see inexperienced developers hopping onto Claude to be
hyper productive but have limited insight how to apply that in the complex
enterprise landscape like LBG.
· Feedback for few profiles:
· the first guy xxxxx - very terse, difficult to get coherent
responses, very narrow exposure to SDLC - talked about agile but not the
process of delivery - not a leader/shaper, a mid to junior level developer with
claude on cv.
· The second guy xxxxxx- had good/relevant experience some
years ago, was better conversatonally, but lacked the kind of sharp/concise and
relevant responses to direct questions about Enterprise SLDC, considerations
towards agentic, etc. No doubt he has a rich career but don't see him
facing into the CTO/CDAO leaders to address a particular complex assertion and
value proposition. On reading the CV's i did have high hopes for those 2 but
unfortunately the interviews lacked substance.
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