Agentic Solutions Architect
New
United States, Eastern TimeFull-TimeSenior
Salary170,500 - 225,000 USD per year
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Job Details
- Experience
- 10+ years of experience architecting large-scale, cloud-based enterprise systems
- Required Skills
- PythonC#LLM
Requirements
- 10+ years of experience architecting large-scale, cloud-based enterprise systems, including data pipelines and AI/ML workloads.
- 6+ years of hands-on software engineering experience with distributed cloud architectures (e.g., Databricks, Spark, EMR, or similar).
- 2+ years of production experience designing and deploying LLM-based solutions (RAG, prompt engineering, evaluation, or model gateways).
- 1+ year of hands-on experience building agent-based or multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
- Strong expertise in C#, Python, or comparable backend languages, with deep understanding of cloud-native design patterns.
- Experience designing secure systems handling sensitive data (PII/PHI) with strong governance and compliance requirements.
- Proven ability to define architecture standards, lead technical decisions, and align stakeholders across multiple teams.
- Strong communication, leadership, and facilitation skills, with experience mentoring engineers and guiding technical direction.
- Familiarity with Agile/SAFe environments and modern DevSecOps, LLMOps, or MLOps practices.
Responsibilities
- Lead end-to-end architecture of enterprise agentic AI and LLM-based systems, defining scalable, secure, and high-performance solutions.
- Design multi-agent frameworks, including orchestration, tool use, memory structures, and human-in-the-loop workflows.
- Evaluate and select technologies such as LLMs, vector databases, agent frameworks, and orchestration platforms to support solution needs.
- Establish governance frameworks covering prompt management, guardrails, bias mitigation, auditability, and regulatory compliance.
- Drive integration across cloud platforms, APIs, CI/CD pipelines, identity systems, and monitoring tools.
- Collaborate with stakeholders across engineering, compliance, and business units to align technical solutions with mission objectives.
- Mentor engineering teams and contribute to architectural leadership, including acting as deputy chief architect when needed.
- Lead continuous optimization of AI systems, ensuring performance, cost efficiency, and scalability across deployments.
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