Company
Technology
SeniorAISystemsArchitect
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior AI Systems Architect. Skills: AI Systems Architecture, Agent-based systems, LLM performance, AI agents. Design AI-driven workflows. Orchestrate AI-driven workflows”
What You'll Achieve.
Reduce hallucinations
Industry & Context.
Analytical thinking; Problem-solving ability
What They're Looking For.
Must Have
Software Architecture background, Platform Engineering background, Senior Software Engineering background, Enterprise-scale systems experience, Designing distributed systems, Designing APIs, Designing microservices architectures, Agentic AI workflows experience, AI engineering experience, Applying LLMs in SDLC, Prompt engineering expertise, Context management expertise, LLM interactions optimization expertise, Translate business logic to workflows, Translate technical knowledge to workflows, Translate business logic to agent heuristics, Translate technical knowledge to agent heuristics, Observability understanding, Monitoring understanding, System behavior analysis understanding, Scalable system design experience, Reliability considerations experience, Performance considerations experience, Analytical thinking, Problem-solving ability, Strategic architectural vision, Advanced English proficiency
Nice to Have
Python development experience, RAG architectures knowledge, MCP exposure, Tool-augmented AI systems exposure, Multi-agent systems experience, Autonomous workflow design experience, Fine-tuning concepts familiarity, Model evaluation concepts familiarity, Datadog experience, Telecom systems background, Billing systems background, Payments systems background, AI platform engineering exposure, Harness engineering exposure, AI-driven SDLC frameworks exposure
What You'll Do.
Design AI-driven workflows
Orchestrate AI-driven workflows
Architect agent-based systems
Promote AI-first approach
Define context management strategies
Define prompt engineering strategies
Define token optimization strategies
Structure knowledge bases
Maintain knowledge bases
Structure architectural decision records
Maintain architectural decision records
Structure technical documentation
Maintain technical documentation
Develop evaluation frameworks
Monitor agent quality
Monitor agent accuracy
Monitor agent behavior
Drive continuous improvement
Reduce hallucinations
Ensure compliance with standards
Ensure compliance with security policies
Ensure compliance with architectural governance
Act as technical reference
Guide AI platform evolution
Guide multi-agent ecosystem evolution
How You'll Work.
Communication Scope
Technical documentation
Full Job Description
## Accountabilities Design and orchestrate end-to-end AI-driven workflows across the software development lifecycle, from requirements definition to deployment, operations, and continuous improvement. Architect agent-based systems that enable autonomous execution of engineering tasks, promoting an AI-first approach to software delivery. Build and evolve specialized AI agents for development, QA, DevOps, product management, and operational support functions. Define strategies for context management, prompt engineering, and token optimization to ensure efficient and reliable LLM performance. Structure and maintain knowledge bases, architectural decision records (ADRs), and technical documentation to ensure consistency and reuse across AI systems. Develop evaluation frameworks (Evals) to monitor agent quality, accuracy, and behavior, driving continuous improvement and reducing hallucinations. Ensure compliance with internal standards, security policies, and architectural governance across all AI-driven systems. Act as a technical reference for the evolution of AI platforms and multi-agent ecosystems applied to software engineering. Requirements: Strong background in Software Architecture, Platform Engineering, or Senior Software Engineering roles with enterprise-scale systems experience. Proven experience designing distributed systems, APIs, and microservices-based architectures. Hands-on experience with Agentic AI workflows, AI engineering, or applying LLMs within the software development lifecycle. Strong expertise in prompt engineering, context management, and optimization of LLM interactions. Ability to translate business logic and technical knowledge into structured workflows and agent-based heuristics. Solid understanding of observability, monitoring, and system behavior analysis in production environments. Experience with scalable system design and engineering best practices, including reliability and performance considerations. Strong analytical thinking, probl
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