Agentic AI Frontier Engineer Associate Director

Cognizant

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Austin, TX
Salary: $185,000–$200,000 / yr
Posted: 9 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $211k

This role $192k

$145k $275k

below market most similar roles pay here above market

This role pays less than 60% of similar roles. Most pay $167,715–$254,187 — the blue band above. At the midpoint, this role pays about $192k versus about $211k for comparable roles.

Based on 240 similar postings.

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About Cognizant

Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.

Cognizant currently has 397 open roles on FindRole.

Listed pay typically runs $100,000–$135,000 across 262 roles with salary data.

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TL;DR · Agentic AI Frontier Engineer Associate Director

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JOB TITLE: Agentic AI Frontier Engineer - Associate Director - 68938091 As an Agentic AI Frontier Engineer - Associate Director - 68938091, you will lead the end-to-end architecture and engineering of Agentic and Generative AI solutions for enterprise clients. You will design multi-agent systems capable of autonomous task planning, execution, and reflection while embedding human-in-the-loop controls and Responsible AI principles. Your daily work involves architecting data ingestion, vector stores, prompt engineering, retrieval-augmented generation, and agent orchestration frameworks. You will utilize large language models, APIs, microservices, and cloud-native platforms including Google Cloud Platform, Microsoft Azure, and Amazon Web Services. The role focuses on solving complex business problems by moving beyond experimentation to build, deploy, and govern scalable, secure, and responsible intelligent systems. You will also provide technical leadership for production deployments and mentor engineering teams.

Skills

Generative AI Agentic AI LLMs RAG Vector Databases Prompt Engineering Agent Orchestration MLOps LLMOps Google Cloud Platform Microsoft Azure Amazon Web Services Microservices APIs Containers Event-driven Systems Cloud-native Platforms Responsible AI

What you'll do

Architect multi-agent systems capable of autonomous task planning, execution, reflection, and escalation within defined guardrails.
Design end-to-end Gen AI architectures including LLM selection, agent orchestration, memory, and human oversight mechanisms.
Define technical architectures for data ingestion, vector stores, prompt engineering, RAG, and integration layers.
Embed Responsible AI principles such as fairness, explainability, transparency, and kill-switch mechanisms into solutions.
Translate business use cases into AI solution blueprints, reference architectures, and implementation roadmaps.
Support pre-sales, RFPs, and solutioning by articulating Agentic AI value propositions to stakeholders.
Provide technical leadership to delivery teams across PoCs, pilots, and production deployments.
Contribute to internal accelerators, reusable assets, and best practices for scaling enterprise AI adoption.

What we're looking for

10+ years of experience in enterprise architecture, frontier engineering, AI engineering, or related technology leadership roles.
Recent experience focusing on Generative AI and Agentic AI.
Hands-on knowledge of LLMs, prompt engineering, RAG, vector databases, agentic workflows, and agent orchestration frameworks.
Experience designing AI, machine learning, or GenAI systems on hyperscaler platforms like GCP, Azure, or AWS.
Strong understanding of API-driven architectures, microservices, event-driven systems, cloud-native platforms, containers, MLOps, and LLMOps.
Ability to communicate complex technical concepts to business, technical, and executive audiences in client-facing or consulting environments.
Master’s degree or Doctor of Philosophy degree in Computer Science, Engineering, or a related STEM field (preferred).

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