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Tier-1 employer and mid-level experience requirement increase competition, niche AI specialization moderates it.
Specialized LLM/AI agent, vector DB, and orchestration expertise required, making cross-industry transferability low.
Explicit 5+ years plus many mandatory AI/ML, cloud, and orchestration technical requirements.
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Lead design and implementation of AI-driven multi-agent SDLC frameworks focusing on code generation, testing, and observability on AWS.
Develop orchestration layers and integrate AI agents with toolchains such as Jira, Bitbucket, GitHub, Terraform, and monitoring platforms.
Provide technical leadership and governance to drive adoption of AI-assisted engineering practices improving code quality, delivery speed, and operational outcomes.
5+ years of applied software engineering experience with formal training or certification.
Strong proficiency in Python, Pydantic, FastAPI, LangGraph, Vector Databases, and deploying AI agent solutions on AWS (EKS, Lambda, S3, Terraform).
Experience with LLM integration, prompt engineering, and AI Agent frameworks (e.g., Langchain, LangGraph, Autogen, MCPs, A2A).
Experience in CI/CD, Terraform, Kubernetes, Docker, APIs, and familiarity with observability/monitoring platforms.
Experienced in architecting and delivering AI-native software products with multi-agent orchestration at scale in cloud environments.
Proven ability to lead and mentor engineering teams on enterprise AI-assisted software development tools and responsible AI governance.
Strong familiarity with secure and compliant AI workflows, emphasizing resilient, secure coding and validation standards in engineering processes.