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Metro location, broad AI/ML/full-stack platform skills, and popular agentic AI role drive high applicant competition.
Specialized ML/AI platform and .NET/agent orchestration requirements create strong domain-specific hiring bias.
Requires 7+ years and mandatory ML, .NET, cloud, and LLM platform experience.
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Design and develop scalable AI platform services, APIs, and SDKs with a .NET and Python codebase to support agentic AI workflows and GenAI-powered applications.
Build multi-agent orchestration, lifecycle management, and production-grade retrieval augmented generation (RAG) pipelines including knowledge retrieval and vector search.
Ensure secure, multi-tenant AI platform capabilities with governance, observability, real-time APIs, and cost optimization across enterprise-grade AI workloads.
7+ years of software engineering experience specializing in ML, Python, agents, and .NET platform development.
Experience with scalable backend platforms, microservices, distributed systems, and cloud-native applications using AWS, Kubernetes, Docker, REST APIs, and CI/CD.
Hands-on expertise with LLMs, Agentic AI, RAG architectures, LangChain, LangGraph, Amazon Bedrock, OpenAI, Anthropic, or similar AI frameworks.
Not explicitly mentioned in the JD: Notice period or mandatory degree requirements.
Experienced AI/ML engineer with full-stack capabilities, proficient in Python and .NET for building cloud-native distributed systems.
Skilled in modern AI orchestration techniques, prompt engineering, vector databases, and enterprise AI security and governance.
Capable of collaborating across product, engineering, and DevOps teams to create reusable AI platform capabilities and accelerate AI adoption in enterprise environments.