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Strong Tier-1 brand, mid-level experience, and Bengaluru location increase candidate competition significantly.
Role requires specialized LLM/agent and RAG expertise, making cross-industry transferability limited.
Explicit 5+ years plus mandatory LLM/agent, cloud, and infra skills create strict shortlisting filters.
Lead design and implementation of LLM-driven AI agent services and multi-agent orchestration on AWS.
Integrate AI agents with development toolchains (e.g., Jira, Bitbucket, Github, Terraform) and monitoring platforms to enhance engineering workflows.
Provide technical leadership and drive adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes across teams.
5+ years of software engineering experience with applied expertise in AI technologies.
Strong hands-on Python skills with frameworks like Pydantic, FastAPI, LangGraph, and vector databases for RAG-based AI agent solutions.
Experience with AWS services (EKS, Lambda, S3) and infrastructure as code tools like Terraform; plus CI/CD, Kubernetes, Docker, and API knowledge.
Proven experience leading use of enterprise AI-assisted software development tools and knowledge of responsible AI engineering practices (security, data sensitivity).
Experienced in full lifecycle development of AI agent solutions using multi-agent orchestration frameworks on cloud-native AWS environments.
Able to autonomously solve complex design and functionality issues with minimal oversight, mentoring junior engineers and leading technical adoption.
Skilled at setting and enforcing standards for AI-assisted development workflows focusing on security, compliance, and measurable quality improvements.