Generative AI Software Architect – Sr. Consultant
| Company | Visa |
|---|---|
| Location | Austin, TX, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, MBA, JD, MD |
| Experience Level | Senior, Expert or higher |
Requirements
- 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.
- 5+ years of experience as a software architect, in designing and implementing scalable, secure, and resilient architectures for enterprise-grade global applications.
- 3+ years of hands-on experience in architecting and deploying AI, ML, GenAI based enterprise solutions, including the integration of large language models (LLMs) and agentic frameworks to automate complex workflows, enhance decision-making, and deliver personalized user experiences.
- Proven track record of delivering highly resilient enterprise solutions.
- Proven architectural expertise in building conversational agents with short-term memory (context windows, session state) and long-term memory (vector stores, memory graphs).
- Deep architectural knowledge of LLM orchestration frameworks (e.g., LangGraph, CrewAI, Semantic Kernel) and multi-agent systems.
- Familiarity with multi-agent GenAI solutions that incorporate agentic behaviors using A2A and MCP protocols.
- Experience with vector databases (e.g., Pinecone, ChromaDB), embedding models, and RAG pipelines.
- Experience in retrieval-augmented generation (RAG) pipelines, hybrid search strategies, and embedding optimization.
- Experience with DevOps/MLOps practices, CI/CD pipelines, and version control systems.
- Proven ability to lead cross-functional AI initiatives, including PoC development, stakeholder alignment, and enterprise rollout.
- Excellent communication skills with the ability to translate complex technical concepts to business stakeholders.
Responsibilities
- Define and evolve the enterprise-wide architecture blueprint for GenAI and agentic systems.
- Lead the design of modular, reusable, and scalable architecture patterns for GenAI and agentic applications.
- Design single pane of Glass GenAI product(s) which caters to multiple corporate domains and multiple personas.
- Develop and design robust, secure solution patterns that can be operationalized across enterprise environments.
- Architect and implement agentic AI systems using frameworks like LangGraph, LangChain, or CrewAI.
- Design agent coordination strategies and evaluation pipelines for autonomous enterprise workflows.
- Develop architectural patterns for advanced prompt engineering, including dynamic prompt templates and multi-turn dialogue strategies.
- Implement intent analysis techniques to enhance agent decision-making and user interaction quality.
- Demonstrate deep understanding of various LLM models (e.g., GPT, Claude, Gemini, open-source models) and determine the right model for each use case based on performance, cost, latency, and compliance.
- Rapidly develop PoCs and iterate solutions using an agile, experimental approach—without compromising architectural integrity or long-term scalability.
- Build cloud-native, containerized infrastructure (Kubernetes, ECS, EKS) for deploying GenAI models at scale.
- Integrate CI/CD pipelines, model versioning, and automated testing for continuous delivery.
- Design APIs and microservices to integrate GenAI capabilities into enterprise systems (ERP, CRM, HRIS).
- Architect solutions that are highly secure and have High availability, resiliency, uptime, and built-in insights.
- Establish monitoring frameworks for agent behavior, hallucination detection, and model drift.
- Stay ahead of trends in agentic AI, autonomous systems, and LLM orchestration.
- Lead internal workshops, and innovation sprints to explore new use cases.
- Maintain detailed architectural documentation and operational playbooks.
- Mentor engineering teams and promote best practices in GenAI development.
Preferred Qualifications
- 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD.