Custom Software Engineer

Overview

Own the automation architecture for application support operations and lead delivery using Python, Generative AI and Agentic AI, converting incidents, requests, batch, observability and alert opportunities into reusable workflows.

What you'll do

• Define and govern automation architecture across ITIL phases, including HLD/LLD and standards.
• Act as design authority and SME for Python automation, GenAI and Agentic AI, owning design decisions.
• Build agent orchestration, tool calling, RAG over runbooks, and knowledge assistants.
• Automate ticketing (triage, routing, auto-remediation, RCA) and non-ticketing work (batch, health checks, data fixes, access, reports).
• Apply SRE and observability practices: SLI/SLO, golden signals, self-healing and alert noise reduction.
• Govern integrations, CI/CD, coding standards and Responsible AI guardrails.
• Build the automation business case, present outcomes and mentor the team.

What you'll need

• Bachelor's degree or equivalent experience, with 15 years of full-time education.
• Minimum 12 years of experience (must-have skill: Python).
• 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 skills: prompt engineering, RAG, LLM integration, guardrails.
• Agentic AI experience with LangChain, LangGraph, AutoGen or CrewAI on Azure OpenAI or Bedrock.
• REST API, JSON, SQL, scripting integration and event-driven design.
• SRE, event correlation and observability (Dynatrace, Splunk, Grafana, ELK), DevOps/CI-CD and ITIL.
• Stakeholder management and business outcome articulation with client architects and leadership.

Nice to have

• Generative AI (good-to-have skill).
• Vector databases (Azure AI Search, Pinecone, ChromaDB, FAISS), knowledge graphs, and cloud (Azure, AWS, GCP).
• Preferred certifications in Python, cloud, Generative AI, ITIL or observability.

Details

• Location: India or Global Delivery Center locations.
• Work mode: hybrid.
• Success measures: assets deployed, effort and ticket reduction, MTTR and alert noise.