Role Description:

This role is responsible for designing, orchestrating, and operating agentic AI workflows throughout the Software Development Life Cycle (SDLC). The focus is on using and coordinating AI agents (LLMbased tools, code assistants, documentation agents, test case generators, log analyzers, etc.) to accelerate delivery, improve quality, and reduce manual work across requirements, design, development, testing, deployment, and operations.

S/He understands SDLC in practice and is highly skilled at leveraging agentic AI to augment teams (BAs, developers, testers, product managers, DevOps), rather than building AI models from scratch.

Key Accountabilities & Responsibilities:

- Map SDLC (requirements design build test deploy operate) and identify highimpact AI use cases.
- Design and run agentic workflows for:
- Generating/refining requirements, user stories, and acceptance criteria.
- Drafting technical specs, diagrams, and interface contracts.
- Accelerating coding, code review, and refactoring.
- Creating and maintaining test cases and test data.
- Summarizing logs, incidents, monitoring data, and producing release notes/runbooks.
- Integrate AI agents with our toolchain (e.g., Jira/Azure DevOps/Linear, GitHub/GitLab/Bitbucket, test management tools, Confluence/Notion, CI/CD and observability tools).
- Build and maintain prompt libraries and context strategies so agents follow our standards and architecture guidelines.
- Define quality criteria, humanintheloop review steps, and guardrails for safe AI use (accuracy, security, privacy).
- Train and support teams on effective use of agentic AI; create playbooks and SOPs for AIenabled SDLC.
- Track KPIs (cycle time, defect leakage, test coverage,



documentation quality) and continuously improve workflows.

Key Competencies & Skills required

Technical Skills

- Solid understanding of SDLC in practice (Agile/Scrum/Kanban) across requirements, design, build, test, deploy, operate.
- 2-4 years in a software delivery role (e.g., Business Analyst, Developer, QA Engineer, Product Owner, Tech Lead, or Process/Automation Lead).
- Handson experience with advanced AI assistants or agent frameworks (e.g., OpenAI tools, LangChainbased agents, orchestration platforms).
- Ability to design and refine prompts and set up AIdriven workflows (singleagent and multiagent).
- Comfortable working with Gitbased workflows, issue trackers, CI/CD, and common SDLC tooling.
- Strong analytical and processdesign skills; excellent written communication.

Nice to have:
- Experience introducing automation or AI tools into development teams.
- Background in process improvement, DevOps, or engineering productivity.
- Exposure to test automation, observability/log analysis, or technical documentation.

Behavioral Skills:
- Strong analytical and problem-solving skills
- Ability to work in evolving environments
- Good communication skills able to explain AI concepts clearly

Previous Experience & Qualifications

Minimum Educational Qualification

- Bachelor or Master degree in information technology,Computer Science, or a related field.

Certification if any: Years of Experience & Knowledge:
- 2-4 years of experience in IT/Computer Science
- Experience working in enterprise hybrid IT environments with multiple stakeholders across jurisdictions.
- Exposure to Automation, production ready AI solutions
- Strong collaboration with business and technical teams

📌 Agentic AI (Mumbai)
🏢 ERGO Technology u0026 Services
📍 Mumbai