We are standing up an enterprise AI capability across our product organization, and we are looking for a seasoned technical lead to drive it end to end. This is a hands-on role: you will set the technical direction, architecture, and standards, mentor engineers, and steer external delivery partners - while still writing code, building reference implementations, and personally unblocking the hardest problems.
This is a remote-based position located in the United States or Canada. Please note that as part of the recruitment and hiring process, there is an in-person meeting that will take place.
What You'll Do
Enterprise platform rollout & enablement
- Own the architecture and rollout of the enterprise AI platform across the product organization.
- Build and operate cost-effective infrastructure: model garden setup, budget controls and cost monitoring, model tiering, and fallback open-source models.
- Stand up and harden platform foundations - identity federation/SSO, IAM, tenant isolation, security and compliance guardrails, and observability.
- Enable users to adopt off-the-shelf capabilities (e.g., NotebookLM, enterprise search, code assistants) and provide the training and ongoing support that drives real adoption.
- Design and deliver a self-service "agent factory" - patterns, templates, and in-IDE guardrails - so teams can build and maintain their own agents safely.
Product development lifecycle agents
- Lead the design and build of agent workflows across the PDLC:
- Ideation: requirement ideation and generation, design specification generation.
- Development: coding assistants, source-code management.
- Deployment: CI/CD, deployment, and monitoring.
- Partner directly with product, engineering, and other business teams to understand their requirements and help build out their use-cases - not just ship infrastructure but drive measurable productivity gains.
- Establish evaluation, quality, and monitoring practices for agent workflows from sandbox to production.
Cross-platform interoperability
- Build agents that interoperate with agents on other enterprise AI platforms, including cross-platform contracts, schema/intent mapping, and cross-perimeter authentication.
- Represent the product organization technically when working with other business teams on cross-platform agent designs.
Across all tracks - leadership & hands-on
- Own the technical strategy, standards, patterns, and guardrails for agentic workflow development, RAG, security, and governance.
- Lead and mentor a team across cloud and enterprise AI tracks; raise the bar through code review, pairing, and design reviews.
- Steer external delivery partners - scope work, review deliverables, and hold them to quality and timeline.
- Stay hands-on: build reference agents, RAG pipelines, integrations, and MCP connectors, and debug the hardest pieces (including non-deterministic retrieval/generation behavior).
Required Qualifications
- 10+ years of software engineering experience, with 4+ years in a technical lead or staff-level role.
- Strong, current hands-on coding ability - you still build and ship. Proficiency in Python (and comfort across at least one other modern language).
- Experience designing and operating production AI/ML or LLM-based systems: agents, RAG, prompt/eval pipelines, or similar.
- Deep familiarity with Google Vertex AI / Gemini and the surrounding services (IAM, networking, observability, cost management).
- Experience building developer-facing platforms or internal tooling, and driving adoption with training and support.
- Experience integrating systems via APIs and connectors; comfort with authentication and identity federation (OAuth, SSO, workload identity).
- A track record of leading technical initiatives across teams and influencing without authority.
- Strong communication skills - able to work directly with both engineers and non-technical business stakeholders.
Preferred Qualifications
- Hands-on with Gemini Enterprise, Vertex AI, NotebookLM, or comparable enterprise AI tooling.
- Experience building agentic systems and orchestration (agent development kits, A2A protocols, MCP, tool/function calling).
- Experience with LLM gateways and routing (e.g., LiteLLM), model cost optimization, and multi-model fallback strategies.
- Experience managing or working alongside systems integrators / delivery partners.
- Familiarity with the modern PDLC toolchain (Jira/Confluence, Figma, GitHub, CI/CD) and AI coding assistants.
- Experience with AI governance, guardrails, data privacy, and compliance in an enterprise setting.
#LI-Remote
The base pay range for this position varies based on the geographic location. More information about the pay range specific to candidate location and other factors will be shared during the recruitment process. Individual pay is determined based on location of residence and multiple factors, including job-related knowledge, skills and experience.
San Francisco Bay Area:
156,400 - 265,700 USD Annual
All Other US Locations:
136,000 - 231,000 USD Annual
As a part of the total compensation package, this role may be eligible for a bonus. For information on our benefits click here.
