If anyone interview pls drop the resume along with Available time for interview for AI boot interview Mail id : [email protected] Name: CTC: ECTC: NP: looking for immediate to 15 days

Location:
All Hexaware location JD: Mandatory

skills:
Strong Python backend development. Built GenAI applications using OpenAI/Azure OpenAI. Experience with LangGraph or similar agent orchestration frameworks. React frontend skills. Azure cloud deployment experience. RAG/vector database implementations. Docker and CI/CD knowledge. Public GitHub showcasing AI projects. Detailed JD:

Job Description
Role
• FDE Agentic SDLC Developer Role Summary: Exp : 59 yrs Solid in at least one of Java / .
NET / Python / JavaScript-TypeScript; Git, CI/CD, test automation, containers and worked on public Cloud platform Work fluently inside an agentic coding tool (Claude Code, Copilot, Cursor): task decomposition, iterative steering, and knowing when to restart a loop Repo and spec grounding, retrieval over enterprise context, prompt and instruction file design Own a workstream end-to-end in the client codebase. Configure the agentic stack for the client’s tech stack: custom skills, reusable prompts, hooks, sub-agents,



and instruction hierarchies Build MCP servers exposing client systems (repos, ticketing, test management, APIs, data) as agent tools Engineer context at repo scale: grounding in large codebases, retrieval over enterprise docs, and scoping strategy Match model to use case in practice: reasoning models for planning and refactoring, fast/low-cost models for bulk edits and tests, long-context models for codebase comprehension; measure rather than assume Know when prompting and context are enough vs. when fine-tuning or an SLM is warranted, and understand fine-tuning cost: clean labeled data volume, curation effort, eval set, retraining cadence Drive legacy comprehension through agent-led reverse engineering into specs, then modernize from those specs Wire AI output into CI/CD and quality gates: SAST, coverage, and review policy for agent-authored change Build verification harnesses so output is provably correct, not plausibly correct Onboard and pair with client developers; convert one-off tricks into pod assets Handle secrets, PII, and data residency when connecting agents to client systems

📌 FDE -Hexaware (Virtual interview) (Bengaluru)
🏢 Hexaware Technologies
📍 Bengaluru