Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : Python (Programming Language)

Good to have skills : Generative AI

Minimum 12 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

Owns the automation architecture for application support operations and leads delivery using Python, Generative AI and Agentic AI. Converts opportunities across incidents, requests, batch, observability and alerts into reusable workflows.

Roles & Responsibilities:

Architecture — Define and govern automation architecture across ITIL phases: HLD/LLD and standards.

Design authority — SME for Python automation, GenAI and Agentic AI owns design decisions.

GenAI/Agentic AI — Agent orchestration, tool calling, RAG over runbooks, knowledge assistants.

Automation scope — Ticketing (triage, routing, auto-remediation, RCA) and non-ticketing (batch, health checks, data fixes, access, reports).

SRE/observability — SLI/SLO, golden signals, self-healing, alert noise reduction.

Engineering discipline — Govern integrations, CI/CD, coding standards, Responsible AI guardrails.

Leadership — Build the automation business case, present outcomes and mentor the team.

Professional & Technical Skills:

Must-have skills

Advanced Python with enterprise automation architecture and hands-on GenAI and Agentic AI development.

10+ years in software or automation engineering with production assets and architecture ownership.

GenAI: prompt engineering, RAG, LLM integration, guardrails. Agentic AI: LangChain, LangGraph, AutoGen or CrewAI on Azure OpenAI or Bedrock.

REST API, JSON, SQL and scripting integration and event-driven design.

SRE, event correlation, observability (Dynatrace, Splunk, Grafana, ELK), DevOps/CI-CD, ITIL.

Stakeholder management and business outcome articulation with client architects and leadership.

Good-to-have skills

Vector databases (Azure AI Search, Pinecone, ChromaDB, FAISS), knowledge graphs, cloud (Azure, AWS, GCP).

Additional Information:

India or Global Delivery Center locations, hybrid 15 years full-time education.

Preferred certifications: Python, cloud, Generative AI, ITIL or observability.

Success measures: assets deployed, effort and ticket reduction, MTTR and alert noise.