AuxoAI Logo

AuxoAI

Principal Forward Deployed Architect, GCP

Posted 20 Days Ago
Remote
Hiring Remotely in United States
Expert/Leader
Remote
Hiring Remotely in United States
Expert/Leader
Owns end-to-end architecture and technical outcomes for enterprise Gemini AI deployments on GCP. Designs the GenAI platform, agent ecosystem, context graph, data foundation, governance, runtime, and adoption strategy. Advises executives, leads architecture reviews, resolves cross-track tradeoffs, owns technical proposals and estimates, manages delivery risk and costs, and develops delivery teams. Requires production GenAI delivery, cloud architecture, graph and semantic data expertise, regulated-environment experience, and senior client engagement leadership.
The summary above was generated by AI


About AuxoAI 

AuxoAI is building the Forward-Deployed AI Company. The company works alongside Global 2000 enterprises to understand how their businesses operate, reimagine how work gets done with AI, and build production systems that deliver measurable business outcomes. AuxoAI has a unique approach of forward deploying teams of AI strategists and engineers, and accelerating deployment with Damia, its IP FDE workbench. 

Headquartered in the San Francisco Bay Area, AuxoAI is an AI-native Google Gemini Enterprise transformation partner and an AWS advanced-tier partner. Learn more at www.auxoai.com.

 

The Role

You are the person a client trusts to turn an ambitious Gemini Enterprise vision into a business outcome that lasts. As Principal Forward Deployed Architect on an account, you own the result -- the value the client set out to create — and with it the technical whole that produces that value: the GenAI platform foundation on Google Cloud, the agent landscape built on the Gemini Enterprise Agent Platform (GEAP), the context-graph and data foundation those agents reason over, and the enterprise rollout into the Gemini Enterprise app. 

Where specialist engineers each own an individual agent, MCP server or data pipeline, you own the whole — deep in the agent platform and the context / data foundation, fluent enough across governance, runtime and adoption to design, sequence and defend the program end to end. You are the senior technical counterpart the client's executives call before they have decided what to build; more importantly, you are the reason they keep calling. You make Google Cloud's AI foundation deliver the outcomes. 

This role exists because standing up a production agent ecosystem on GEAP is not a single-layer problem — model choice, agents, grounding graph, governance perimeter and change management are load-bearing on one another — and because our largest clients will accept only one senior technical owner rather than several.

Placed at one large Gemini Enterprise account, or holding technical ownership across two or three smaller concurrent engagements. You may direct AuxoAI delivery teams, including offshore and onshore Forward Deployed Engineers and client engineers, on the same program — you own the design coherence across it. Significant pre-sales involvement is expected: the GEAP target architecture, the GCP landing-zone approach, effort estimates, and the technical case in proposals for the practice's largest Gemini opportunities. 



What you will do

Whole-program architecture 

  • Own the target architecture across four layers — GCP GenAI platform foundation, the GEAP agent landscape, the context-graph / data foundation, and enterprise adoption — and sequence delivery across all four. 
  • Set the reference patterns for how agents are built (ground-up in ADK vs. forked and hardened from Agent Garden templates), where they run (Agent Engine managed vs. Cloud Run vs. self-managed GKE), how they are isolated (sandbox strategy), and how they are governed. 
  • Design the context-graph foundation — BigQuery, BigQuery graph (GQL) and/or Spanner Graph — and the grounding / RAG strategy that connects it to agents, including entity resolution, semantic modelling and retrieval over Vertex AI Vector Search. 
  • Identify decisions in one layer that are load-bearing for others (e.g., a grounding-data residency choice that constrains the runtime target and the governance perimeter) and force them to resolution before delivery commits, not during it. 
  • Arbitrate cross-track trade-offs where multiple Forward Deployed Engineers are deployed to the same client, with a written rationale. 
  • Maintain technical proximity: review agent designs and evaluation results, interrogate trajectory and latency behavior, participate in incident reviews, and perform selective hands-on work where it materially changes the outcome. 
  • Represent AuxoAI in the client's security, compliance and architecture review boards, including the model-governance and data-governance forums. 

Client and commercial 

  • Advise client executives on trade-offs, sequencing, delivery risk and what not to build — including which use cases are not yet safe to automate. 
  • Own the technical scope, estimate and defense of proposals and statements of work for the account and for major Gemini Enterprise prospects. 
  • Give Auxo AI leadership an accurate read on delivery risk, including remediation plans and consumption-cost exposure (runtime vCPU-hours, Sessions and Memory events, model tokens, sandbox compute). 

Enablement and practice contribution 

  • Enable the client's own platform, data and security leadership to operate and extend the agent landscape and context graph, with named client owners for each major component. 
  • Develop the Forward Deployed Engineers working alongside you on the account, whether or not they report to you. 
  • Contribute GEAP reference architectures, context-graph patterns, estimation models and governance blueprints that raise the practice standard. 


You are accountable for the outcome, not the artifact. Long after Auxo AI rolls off, the client's agent ecosystem has to keep earning its place — grounded, governed, evaluated and adopted, still delivering the business result it was built for. When an agent delivered under your architecture regresses, leaks data, breaches a policy or loses the users it was meant to serve, you own the explanation to the client and the plan to make it right. 




Requirements

What you will bring

  • Master's degree in Computer Science, Engineering, Information Systems or a related field, or equivalent practical experience. 
  • 12+ years in engineering, architecture or technical delivery leadership, including senior technical ownership of production systems. 
  • Expert depth in at least two of: the agent / GenAI platform layer, the context-graph and semantic-modelling layer, the cloud data-platform layer, and the cloud runtime / governance layer — with working competence across the rest, demonstrable through an architecture walkthrough. 
  • Delivered at least one production GenAI or agent system on GCP (Vertex AI / Agent Platform) or a directly comparable cloud, including grounding over an enterprise data or knowledge foundation. 
  • End-to-end ownership of technical design for at least two client engagements or major cross-team programs, from discovery through production. 
  • Experience as the single senior technical counterpart to a client's executive team on an engagement of material size. 
  • Hands-on depth in BigQuery and at least one graph or semantic store (Spanner Graph, BigQuery graph, Neo4j or equivalent). 
  • Delivery inside at least one regulated environment, with the ability to describe a design decision the regulation forced. 
  • Experience owning the technical scope, estimate and defence of a proposal or statement of work. 

Nice to have

  • Hands-on with the Gemini Enterprise Agent Platform specifically — ADK, Agent Garden, Model Garden, Agent Engine — or a rapid, demonstrable path to it from adjacent agent frameworks

​

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

 

Auxo.ai is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.

 

​


Similar Jobs

12 Minutes Ago
Remote or Hybrid
306K-381K Annually
Senior level
306K-381K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Leads applied AI research and development for foundation models and large-scale machine learning systems. Partners with data scientists, engineers, product managers, and academic researchers to define research directions, train and evaluate models, optimize inference and training, and deploy AI capabilities into products. Mentors applied scientists and managers, represents the organization externally, and translates advanced research into scalable customer experiences.
Top Skills: Aws UltraclustersCloud ComputingDeepspeedDglGpu ClustersHugging FaceLightningNemoPyTorchPytorch Geometric
12 Minutes Ago
Remote or Hybrid
101K-138K Annually
Senior level
101K-138K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Analyzes business challenges and opportunities for Capital One Shopping, developing strategic recommendations, product and pricing models, credit risk models, marketing insights, and monitoring plans. Leads cross-functional initiatives with IT, Sales, Operations, and Finance to improve growth, profitability, customer experiences, and credit performance. Requires strong quantitative analysis, communication, business judgment, and execution skills.
Top Skills: SQL
14 Minutes Ago
Remote or Hybrid
Chicago, IL, USA
122K-167K Annually
Mid level
122K-167K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Manages workplace violence prevention and threat assessment cases involving associates, assets, and business operations. Conducts investigations, interviews, open-source and social media research, crisis support, case documentation, and threat mitigation planning. Collaborates with Legal, Human Resources, Associate Relations, law enforcement, and other stakeholders. Develops and delivers training on threat assessment, workplace violence, suicide intervention, and intimate partner violence, while participating in rotating on-call coverage.
Top Skills: Open-Source Intelligence (Osint)Social Media Monitoring PlatformsStructured Professional Judgment (Spj)

What you need to know about the Chicago Tech Scene

With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.

Key Facts About Chicago Tech

  • Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
  • Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
  • Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
  • Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account