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Principal AI Platform Engineer

Saransh Inc

📍 New York, New York, United States, UN0💼 Contract🕐 6/11/2026
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Role overview

Saransh Inc is hiring for the Principal AI Platform Engineer role in New York, New York, United States, UN. It is contract, Lead level, in the Tech sector. It was posted 6/11/2026.

On TalentyGo you can review this job and apply more effectively: Charlie prepares an ATS-optimized resume and a cover letter tailored to "Principal AI Platform Engineer" at Saransh Inc in about a minute. Before you apply, you can also check how well your profile fits, with a match score based on skills, experience, location and seniority.

Role
Principal AI Platform Engineer
Company
Saransh Inc
Location
New York, New York, United States, UN
Work mode
On-site
Employment
Contract
Seniority
Lead
Sector
Tech
Posted
6/11/2026

Description

Role : Principal AI Platform Engineer Location: New York City, NY / Alpharetta, GA (Hybrid) Overview Hands-on engineering leadership role focused on AI platforms, LLM systems, and orchestration (with strong IAM/PAM alignment). Key Skills & Background Proficiency With C programming language Unix/Linux systems Knowledge Of Cryptography Authentication & authorization concepts Experience Working In Secured enterprise environments Agile development teams Engineering Skills Python and Perl development Ability to communicate technical concepts to business stakeholders Strong collaboration and independent execution capabilities Contributions to Linux/Unix/open-source projects are valued Knowledge of Kerberos (preferred) Core Responsibilities AI / LLM Platform Engineering Lead hands-on development of AI-enabled and LLM-based applications Build agentic and multi-agent systems Design And Implement Orchestration Architectures Including Function invocation State and memory management Policy-aware execution AI Engineering & Integration Develop Intelligent Agent Workflows Using Prompt design Grounding strategies Tool orchestration layers Platform Ownership Own Full-stack AI System Architecture APIs Data pipelines Model serving and observability Ensure performance, scalability, and reliability across environments Security & Governance Embed Secure-by-design Principles, Including Access controls Logging and traceability Explainability Human-in-the-loop safeguards Drive reviews, mentoring, and best practices for AI engineering Required Skills Hands-on platform engineering experience end-to-end Deep Expertise In LLMs and model lifecycle Prompt engineering and grounding Hallucination mitigation Strong System Design Experience Including Multi-agent architectures Distributed systems Cloud-native development Key Technologies / Areas LLM frameworks and orchestration Cloud platforms and APIs Distributed systems design AI governance framework

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