- Architect, design, and evolve a scalable, secure AI platform and reference architecture that enables rapid development of AI-powered product capabilities
- Drive strategic decision-making across: Model selection and fine-tuning Retrieval-Augmented Generation (RAG) Agent frameworks Data pipelines Inference optimization
- Evaluate and integrate: Open-source and commercial LLMs Vector databases Feature stores MLOps platforms
- Collaborate cross-functionally with Product, Engineering, Architecture, and UX to define AI requirements and priorities
- Lead and influence engineering teams (directly and indirectly), fostering a culture of innovation and architectural excellence
- Lead architecture reviews, technical governance, and long-term platform planning
- Provide architectural direction for Agentic AI systems, including: Workflow orchestration Multi-agent collaboration Context management Safety controls Autonomous decision-making frameworks
- Design and implement LLMOps and AIOps practices for production systems
- Drive observability practices for monitoring agent behavior and system performance
- Define guardrails for: Agent interactions Memory usage Context boundaries
- Define and enforce: Target-state architectures Principles and standards for AI/ML Responsible AI and ethical frameworks (e.g., GDPR, NIST AI RMF)
- Establish processes for metadata extraction and management, enabling granular access control
- Define AI/ML technical capabilities, including: Generative AI systems Data pipelines Model deployment strategies MLOps frameworks
- Develop and maintain AI reference architectures and best practices
- 8+ years of experience as a Senior, Lead, or Principal Engineer/Architect
- Hands-on experience with AI and ML systems in production environments
- Proven ability to lead large-scale architectural initiatives and influence cross-functional decisions
- Strong programming proficiency in: Python (expert-level required) Java, TypeScript, Node.js, or similar
- Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen
- Deep experience with: Large Language Models (LLMs) Embeddings Vector databases RAG architectures Model serving frameworks
- Hands-on experience with Agentic AI patterns, including: Autonomous agents Tool usage Multi-agent coordination Goal-directed planning
- Strong background in cloud platforms: AWS, Azure, or GCP
- Experience with: Containerization Serverless technologies Distributed systems
- Experience designing secure AI systems, including: Data privacy Encryption Compliance Responsible AI practices
- Solid understanding of: API integration patterns Messaging systems Event-driven architectures
- Hands-on experience with: Microservices architectures Domain-driven design (DDD) Platform engineering
- Proven experience building scalable, high-performance distributed systems
- Excellent communication, problem-solving, and technical leadership skills
- Ability to influence and align teams across organizational boundaries
Why Join Us
This is an opportunity to work with cutting-edge AI technologies, solve real business challenges, and shape a forward-looking technology strategy.
If you are passionate about AI and ready to tackle complex and impactful challenges, we encourage you to apply.
Tricentis is proud to be an equal opportunity workplace. Qualified applicants will receive consideration for employment without regard to race, color, ethnicity, gender, religious affiliation, age, sexual orientation, socioeconomic status, or physical and mental disability and other statuses protected by law.
Global Sanctions Compliance
We comply with all applicable global sanctions and export control laws. Candidates must not be listed on any government restricted party lists (including OFAC SDN List and U.S. Commerce Department restricted lists) and must certify that their employment would not violate any sanctions or export control regulations. Candidates must notify us of any changes to their status during the application process or subsequent employment.
U.S. Work Authorization:
This role is not eligible for employer-sponsored work visas. Applicants must be authorized to work in the U.S. without current or future sponsorship.
Similar Jobs
What you need to know about the Austin Tech Scene
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center



