Infrastructure Optimization & AI Technical Lead

The Infrastructure Optimization & AI (IOAI) organization is transforming Enterprise Technology Services (ETS) from reactive operations and manual analysis toward proactive, predictive intelligence and governed Generative AI adoption. At the heart of this mission is the Operational Digital Intelligence Platform (ODP) and its flagship conversational intelligence product family, including AskIT, Ask for Network, and AskIT for NOC.

We are seeking a Technical Lead who bridges the gap between high-level enterprise architecture and hands-on software development. In this role, you will define and implement scalable GCP architectures while actively writing and reviewing high-quality production code. You will serve as the technical authority across our core platform build, guiding cross-functional engineering squads in delivering robust data pipelines, deterministic policy engines, indexing and  retrieval systems, and Google Enterprise AI agentic workflows.

• Architect Scalable Cloud Solutions: Design and implement modular, loosely coupled cloud architectures on GCP that scale independently and adhere to strict enterprise reliability and zero-trust standards.
• Enforce Design Patterns: Establish canonical schemas, interface contracts, and reusable platform patterns across ingestion, normalization, storage, and AI reasoning layers.
• Bridge Architecture & Squad Delivery: Translate product roadmaps and Architecture Review Board (ARB) specifications into actionable engineering milestones, technical spikes, and clear interface contracts.
• Mentor & Guide Squad Engineers: Provide technical mentorship, code reviews, and architectural guidance to squad developers and partner engineering teams (including TCS engineers) across sprints.

• Backend Micro services: Develop high-performance, containerized micro services and jobs using Python (FastAPI, Pydantic v2) hosted on GCP Cloud Run.
• Deterministic Policy Engines: Build deterministic validation and evaluation engines that isolate critical business logic (e.g., CIDR math, precedence rules) from probabilistic LLM outputs to guarantee zero hallucinations on deterministic operations.
• Canonical Data Contracts: Implement strict schema validation and data contracts for ingesting structured and unstructured operational telemetry from systems like GitLab, Palo Alto Panorama, ServiceNow, and GCP APIs.
• Resilience & Idempotency: Design idempotent pipelines, automated quarantine routing for malformed payloads, and self-healing deployment models.

• Agentic Orchestration: Architect conversational agent workflows using Vertex AI Agent Builder, Gemini, and agentic frameworks (e.g., LangGraph), integrating custom tool routing, memory, and complexity routing.
• Knowledge Retrieval & GraphRAG: Implement advanced hybrid retrieval combining Spanner Graph, vector embeddings, and Vertex AI Search to power grounded, multi-hop operational reasoning.
• Grounding & Provenance: Enforce 100% evidence provenance, ensuring all AI-generated responses carry verifiable citations linking back to authoritative rule IDs, commit hashes, or documentation.
• AI Evaluation & Safety Gates: Partner with QA and AI Assurance teams to implement evaluation pipelines (using frameworks like Braintrust) to measure grounding, latency, and enforce safety gates (e.g., zero False ALLOWs on golden corpora).

• Zero-Touch CI/CD: Implement automated testing, container scanning, and zero-touch deployment pipelines to ensure repeatable, immutable cloud releases.
• Security & Access Governance: Enforce Attribute-Based Access Control (ABAC), pre-retrieval entitlement filtering, Secret Manager integration, and Model Armor safety filters.
• Observability & FinOps: Integrate end-to-end tracing across Cloud Logging and Cloud Monitoring; balance compute performance with GCP cost efficiency.

• Hands-On Development Experience: 5+ years of professional software development experience, with deep proficiency in Python (including modern async patterns, typing, and Pydantic v2).
• Cloud Architecture & GCP Expertise: 4+ years of hands-on architecture and engineering experience on Google Cloud Platform, specifically: Serverless Compute & Orchestration: Cloud Run, Cloud Functions, Pub/Sub, Cloud Scheduler.Data & Storage: BigQuery (partitioning, clustering, policy tags), Cloud Storage, and Cloud Spanner (Spanner Graph is a strong plus).Security & IAM: Secret Manager, IAM roles/service accounts, and workload identity federation.
• Modern AI & LLM Systems: Direct experience architecting applications leveraging Google Vertex AI (Gemini models, Agent Builder, Search, grounding pipelines, and vector embeddings) or frameworks like LangChain/LangGraph.
• Data Contracts & System Design: Demonstrated track record designing distributed systems, RESTful APIs, event-driven pipelines, and canonical data models.
• Technical Leadership: Proven ability to lead squads, mentor developers, define architectural standards, and drive consensus across engineering, product, and platform leadership.
• Education: Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or equivalent practical enterprise experience.

• GCP Certifications: Google Cloud Certified Professional Cloud Architect or Professional Data Engineer.
• Network & IT Operations Domain Knowledge: Familiarity with enterprise network concepts (firewalls, CIDR routing), ServiceNow IT Service Management (ITSM/KM), or IT Operations Analytics.
• AI Quality & Benchmarking: Experience building automated LLM evaluation harnesses, prompt regression suites, or synthetic evaluation datasets.
• Financial Services Background: Experience navigating enterprise governance, model risk management, and regulatory compliance within a financial institution.

As Technical Lead within IOAI, you will embody and drive our core engineering principles :

• Zero Trust & Security First: Explicit verification and least-privilege access built into every tier.
• Cloud First & Ephemeral Workloads: Prioritizing disposable, idempotent, and horizontally scalable cloud services.
• Docs as Tests & AI: Treating documentation, run-books, and knowledge articles as governed, testable inputs for intelligent systems.
• Keep It Simple & Reduce Variation: Standardizing reusable patterns over custom, one-off complexity.

COMPENSATION AND BENEFITS

Please click here for a list of benefits for which this position is eligible.

Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.

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