Note: The job is a remote job and is open to candidates in USA. Calix is at the forefront of a generational change in the broadband industry, seeking a seasoned technical lead for their enterprise AI capabilities. The role involves driving the architecture and rollout of the enterprise AI platform, mentoring engineers, and ensuring cross-platform interoperability while remaining hands-on in coding and problem-solving.
Responsibilities
- 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
- 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
- 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
- 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)
Skills
- 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
- 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
Benefits
- As a part of the total compensation package, this role may be eligible for a bonus.
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