Senior Software Architect - Agentic AI Platform

JOB SUMMARY
Define and drive the technical architecture for the enterprise agentic AI platform. Design complex multi-agent systems, evaluate architectural tradeoffs, and build proof-of-concept solutions.

Key Responsibilities
Define and evolve the architecture of the Agentic System Layer.
Design multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines.
Establish enterprise patterns for agent reliability, observability, security, guardrails, and graceful degradation.
Design scalable distributed systems using microservices and event-driven architecture.
Define REST and gRPC API contracts, data-flow patterns, and integration standards across the AI platform.
Build and improve RAG pipelines, prompt-management solutions, tool-calling patterns, and LLM-routing strategies.
Evaluate and integrate agentic AI frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, and AutoGen.
Lead technical design reviews and create Architecture Decision Records (ADRs).
Collaborate with software engineers, ML engineers, and architects to deliver scalable, secure, and maintainable platform components.
Develop code and proof-of-concept solutions to validate architectural decisions.
Support platform development, feature delivery, and production operations.
Participate in Agile ceremonies, architecture discussions, and code reviews.
Mentor engineers on best practices for developing production-grade AI systems.

Required Qualifications
10+ years of software architecture or senior engineering experience.
At least three years of experience designing AI/ML platform systems.
Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies.
Proven experience building and deploying agentic AI systems or LLM-powered applications at production scale.
Strong knowledge of multi-agent orchestration and agent tool-use patterns.
Experience designing RAG pipelines and prompt-engineering solutions.
Strong understanding of agent reliability, observability, evaluation, security, and guardrails.
Deep expertise in distributed systems, microservices architecture, and event-driven design.
Strong API design experience using REST and/or gRPC.
Advanced programming skills in Python.
Proficiency in at least one additional language: Java, Go, or TypeScript.
Ability to evaluate technical tradeoffs and clearly communicate architectural decisions.
Experience leading technical reviews and mentoring engineering teams.

Preferred Qualifications
Kubernetes and container-orchestration experience.
Experience with AWS, Azure, or Google Cloud Platform.
Knowledge of MLOps and LLMOps tools and practices.
Experience with vector databases such as Pinecone, Weaviate, or pgvector.
Knowledge of graph databases or knowledge graphs.
Experience designing multi-agent system patterns.
Familiarity with agent evaluation and benchmarking frameworks.