AI Consultant for Faster SDLC and Measuring SDLC Productivity
We are looking for an experienced AI Consultant / AI Solutions Architect to help us design an AI-first SDLC (Software Development Lifecycle) acceleration strategy for an enterprise environment.
The objective is to identify and propose the best AI tools, frameworks, and workflows across the entire SDLC — from business analysis through to deployment — and define a clear, measurable model for productivity and efficiency gains.
This is not a generic research task. We are looking for someone who can provide practical, enterprise-grade recommendations with a strong understanding of real-world implementation.
Scope of Work
You will be responsible for:
1. AI Tooling Landscape for SDLC
Recommend best-in-class AI tools across:
Business Analysis
Requirements gathering
User story generation
Documentation automation
Development / Coding
Code generation (e.g. copilots)
Code refactoring
Legacy code transformation
Testing & QA
Automated test case generation
Regression testing automation
AI-based bug detection
DevOps & CI/CD
AI-assisted pipelines
Deployment optimisation
Incident prediction / monitoring
Documentation & Knowledge Management
Auto-documentation
Code-to-doc conversion
Knowledge assistants
2. SDLC Workflow Redesign (AI-First)
Redesign a typical SDLC lifecycle using AI at each stage
Identify where manual effort can be reduced or eliminated
Define how tools integrate into a seamless workflow
3. Efficiency Measurement Framework
Design a clear model to measure improvement, including:
Baseline vs post-AI metrics
Developer productivity (velocity, cycle time)
Test coverage & defect leakage
Deployment frequency & failure rates
Cost per feature / release
We want quantifiable ROI, not just qualitative benefits.
4. Implementation Roadmap
Provide:
Phased rollout plan (quick wins → scale)
Tool selection rationale
Integration considerations
Risks and mitigation
Deliverables
AI Tooling Recommendation Report
AI-First SDLC Architecture / Workflow
Metrics & KPI Framework (with measurement model)
Implementation Roadmap (phased approach)
Ideal Candidate
We are looking for someone who:
Has hands-on experience with AI tools in SDLC (not just theoretical knowledge)
Understands modern engineering environments (cloud, microservices, CI/CD)
Has worked with tools like:
GitHub Copilot, Codeium, Cursor, etc.
AI testing tools
DevOps automation platforms
Can think at both:
Strategic level (architecture, transformation)
Practical level (tools, workflows, implementation)
Nice to Have
Experience in enterprise environments (banking, telecom, large-scale systems)
Exposure to AI-driven engineering platforms
Experience quantifying engineering productivity improvements
How to Apply
Please include:
Examples of similar work or projects
Your recommended top 5 AI tools for SDLC (and why)
How you would measure ROI from AI in engineering
Your approach to integrating AI into existing SDLC workflows
Engagement Type
Initial: Strategy & advisory (short-term)
Potential extension: Implementation support
Goal
We want to move toward an AI-driven engineering organisation that delivers faster, with higher quality and lower cost — and we are looking for the right expert to help us define that journey
Apply Now
Apply Now
The objective is to identify and propose the best AI tools, frameworks, and workflows across the entire SDLC — from business analysis through to deployment — and define a clear, measurable model for productivity and efficiency gains.
This is not a generic research task. We are looking for someone who can provide practical, enterprise-grade recommendations with a strong understanding of real-world implementation.
Scope of Work
You will be responsible for:
1. AI Tooling Landscape for SDLC
Recommend best-in-class AI tools across:
Business Analysis
Requirements gathering
User story generation
Documentation automation
Development / Coding
Code generation (e.g. copilots)
Code refactoring
Legacy code transformation
Testing & QA
Automated test case generation
Regression testing automation
AI-based bug detection
DevOps & CI/CD
AI-assisted pipelines
Deployment optimisation
Incident prediction / monitoring
Documentation & Knowledge Management
Auto-documentation
Code-to-doc conversion
Knowledge assistants
2. SDLC Workflow Redesign (AI-First)
Redesign a typical SDLC lifecycle using AI at each stage
Identify where manual effort can be reduced or eliminated
Define how tools integrate into a seamless workflow
3. Efficiency Measurement Framework
Design a clear model to measure improvement, including:
Baseline vs post-AI metrics
Developer productivity (velocity, cycle time)
Test coverage & defect leakage
Deployment frequency & failure rates
Cost per feature / release
We want quantifiable ROI, not just qualitative benefits.
4. Implementation Roadmap
Provide:
Phased rollout plan (quick wins → scale)
Tool selection rationale
Integration considerations
Risks and mitigation
Deliverables
AI Tooling Recommendation Report
AI-First SDLC Architecture / Workflow
Metrics & KPI Framework (with measurement model)
Implementation Roadmap (phased approach)
Ideal Candidate
We are looking for someone who:
Has hands-on experience with AI tools in SDLC (not just theoretical knowledge)
Understands modern engineering environments (cloud, microservices, CI/CD)
Has worked with tools like:
GitHub Copilot, Codeium, Cursor, etc.
AI testing tools
DevOps automation platforms
Can think at both:
Strategic level (architecture, transformation)
Practical level (tools, workflows, implementation)
Nice to Have
Experience in enterprise environments (banking, telecom, large-scale systems)
Exposure to AI-driven engineering platforms
Experience quantifying engineering productivity improvements
How to Apply
Please include:
Examples of similar work or projects
Your recommended top 5 AI tools for SDLC (and why)
How you would measure ROI from AI in engineering
Your approach to integrating AI into existing SDLC workflows
Engagement Type
Initial: Strategy & advisory (short-term)
Potential extension: Implementation support
Goal
We want to move toward an AI-driven engineering organisation that delivers faster, with higher quality and lower cost — and we are looking for the right expert to help us define that journey
Apply Now
Apply Now