Staff Enterprise AI Engineer - Agentic Workflows & Productivity
Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Aug 28, 2026. Calix scores A on the Alion truth index.
We’re at the forefront of a once in a generational change in the broadband industry. Join us as we innovate, help our customers reach their potential, and connect underserved communities with unrivaled digital experiences.
About the Role:
We are standing up an enterprise AI capability across our product organization, and we are looking for aseasoned technical leadto 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.
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 ofagent workflowsacross 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 shipinfrastructure butdrive 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 foragentic workflowdevelopment, 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 / Geminiand 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.
Location:
- India - (Flexible hybrid work model - work from Bangalore office for 20 days in a quarter). Please note that as part of the recruitment and hiring process, there is an in-person meeting that will take place.