Technology Architect | Analytics - Packages | Python - Big Data

Client: Apple

Do you have a pre-identified candidate? New sourcing? Existing Subcon?- New sourcing

Max Hourly #### to the candidate?: ####/Hr

Do you have a preferred interview schedule?: Yes

Would you require the candidates to meet you for an in-person interview?: No

Is Skype/WebEx interview, OK?: Yes

Work Location with ZIP: Sunnyvale-CA-94085

Is remote work an option?: No

If remote work, please indicate how many days are required to be in the office and remote: 3 days in a week required to be in the office

Chance to be perm?: Yes

Performance Expectations:

Technical Hiring Criteria (Must Haves)

Top 3 Required skills: Python, LLM, AI agent frameworks (Google ADK, LangChain )

Years of experience in each of the must-have skills: 8+ Years

Any Certifications required: No

Any additional information you would like to share about the project specs/nature of work: NA

Job Description -
As the Lead Engineer, AI Agents, you will drive the technical vision and execution for a new class of intelligent agent-based systems at Apple.
Lead the end-to-end lifecycle of AI agents, from conceptualization to deployment and operational excellence.
Guide a team of engineers to build and scale sophisticated AI agents that can reason, learn, and act across diverse data landscapes.
Lead the integration of AI agents with I the Apple data and platforms ecosystem.
Tackle complex AI challenges, such as ensuring agent reliability at scale, developing novel evaluation frameworks, and pioneering privacy-preserving agentic architectures.
Partner closely with teams in data science, engineering, operations, and research to translate high-impact opportunities into robust, production-grade solutions.

Minimum Qualification -
8+ years of software development or machine learning experience.
M.S. or PhD in computer science, machine learning, or a related field or equivalent practical experience.
4+ years of experience in a technical leadership role.
Strong programming skills in Python and applied experience with a range of LLMs.
Expert in applying and extending AI agent frameworks (Google ADK, LangChain, etc.).
Hands-on experience developing, deploying, and operating AI agents in production.
Experience deploying AI systems in large-scale, hybrid environments with a focus on performance and reliability.

Preferred Qualification -
A portfolio of deployed agentic systems that have delivered significant, measurable impact.
Experience in evaluation frameworks for AI agents.
Proven expertise in optimizing AI agents for latency, scalability, and cost.
A track record of thought leadership or contributions to the field of agentic AI.

Project Code: Master project code for AMP DSA data ope