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Tier-1 brand, metro locations, and mid-senior level increase qualified applicant competition moderately.
Specialized LLM/agent engineering requires AI domain expertise though Python and cloud skills are moderately transferable.
Explicit 5+ years plus many mandatory AI, cloud, and orchestration tech stack requirements make screening strict.
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Lead design and implementation of AI-driven agent services and multi-agent orchestration frameworks to transform the software delivery lifecycle.
Collaborate with cross-functional teams to build and deploy AI-native SDLC tools and automation on AWS, integrating with existing software engineering toolchains.
Provide technical leadership and governance to adopt AI-assisted engineering practices that improve code quality, delivery speed, and secure coding standards.
5+ years of applied software engineering experience with formal training or certification in software engineering.
Hands-on expertise in Python, Pydantic, FastAPI, LangGraph, vector databases, multi-agent AI orchestration (Langchain, LangGraph, Autogen, MCPs, A2A), and AWS deployment (EKS, Lambda, S3, Terraform).
Experience integrating LLMs and AI agent frameworks within CI/CD pipelines and SDLC toolchains (Terraform, Kubernetes, Docker, APIs).
Demonstrated experience leading enterprise use of AI-assisted software development tools with strong understanding of responsible AI practices and secure coding.
Senior technical leader comfortable architecting and delivering AI-native software engineering platforms in an Agile environment.
Expertise in AI technologies for software engineering including multi-agent systems, LLM orchestration, and AI toolchain integration.
Experience mentoring engineers and driving AI-assisted development standards across teams to accelerate delivery and maintain secure, scalable SDLC environments.