Seeking a hands‑on AI / GenAI Architect / Senior Lead with strong experience designing and implementing enterprise‑scale Generative AI and Agentic AI solutions.
This job delivers complete solutions spanning all phases of the Software Development Lifecycle (SDLC). It involves advising management on project-level issues, guiding junior engineers, operating with little supervision, and applying knowledge of technical best practices.
Locations (3)
San Jose, California, United States
Austin, Texas, United States
Scottsdale, Arizona, United States
Compensation
The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location | Pay Range: San Jose, California: ($143,500.00 - $212,850.00 Annually) Additional Location(s) | Pay Range: Austin, Texas: ($130,500.00 - $193,600.00 Annually) Scottsdale, Arizona: ($123,500.00 - $183,700.00 Annually)
Responsibilities
Acts as a project or system leader, coordinating the activities of other engineers on the project or within the system
Determines the technical tasks that other engineers will follow
Principal Product Manager - AI Observability (Chronosphere)
Lead the team building out AI Observability and Evaluation features used by developers to measure the accuracy, relevance, performance and safety of artificial intelligence models, agents and RAG applications.
Responsibilities
Perform primary research, interviewing end-users and buyers to deeply understand their AI Observability and Evaluation needs and benefits sought.
Partner with engineers and technical stakeholders to articulate, scope, and deliver well integrated AI Observability and Evaluation features and product line extensions.
Build on Chronosphere’s industry leading observability platform to enable the systemic testing, measuring and benchmarking of AI models, particularly Large Language Models and agentic AI applications.
Set KPIs to articulate and measure intended value and impact for customers.
Develop comprehensive roadmaps and deliver plans to achieve stated outcomes for customers and the business.
We are looking for an experienced GenAI Senior Engineer to design, build, and maintain scalable, secure, and production-grade AI platforms and applications.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $120,000-$150,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.
Responsibilities
Design, develop, and maintain scalable, secure, and highly available GenAI platforms and AI-powered applications on AWS.
Architect and implement Agentic AI solutions, multi-agent systems, tool integrations, function calling, and workflow orchestration frameworks.
Design and implement enterprise-grade RAG solutions using embeddings, vector databases, semantic search, reranking, and knowledge retrieval techniques.
Build AI applications leveraging Amazon Bedrock for LLM inference, model orchestration, prompt management, and foundation model integrations.
Develop reusable AI platform components, SDKs, APIs, accelerators, and reference architectures.
Lead the design, development and operationalisation of GenAI models, intelligent agents, copilots and automation solutions across Bupa.
Responsibilities
Lead the design, development and operationalisation of GenAI models, intelligent agents, copilots and automation solutions across Bupa.
Own AI solution delivery end-to-end, from discovery and scoping through to evaluation, build, testing, deployment, monitoring and optimisation.
Oversee technical solution design, integrations, APIs, data flows and model selection, ensuring alignment with Bupa’s AI and architecture standards.
Manage key elements of the AI engineering stack, including LLM platforms, orchestration frameworks, vector databases, retrieval pipelines, security controls and cloud infrastructure.
Partner with business teams to understand their needs and ensure AI solutions deliver measurable value and improved operational outcomes.
Design multi-agent systems that run real business processes and remain governable in production. Own the target architecture for the organization’s agentic ecosystem and ensure reliability, cost, and business outcomes.
Responsibilities
Set the architectural direction for agentic solutions across the enterprise, including approved multi-agent patterns, operating models, and standards
Define how agent components work together across shared data, memory, feedback, observability, identity, and control mechanisms
Partner with business owners to identify and prioritize agent use cases, assess value and risk, and shape the business case
Apply data-driven design and machine learning techniques so agents can improve from outcomes and feedback
Embed evaluation, testing, Responsible AI, security, and governance controls into the architecture from the start
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