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Distinguished AI Engineer – Enterprise AI Platform

Kasmo Inc.Jersey City, NJ🇺🇸United StatesPosted Sep 29, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Jersey City, NJ, United States
Posted
19 hours ago
MLOpsGenerative AIKubernetesLLMTerraform

Job Description

Position: Distinguished AI Engineer – Enterprise AI Platform

Location: Jersey City, NJ
Work Arrangement: Onsite 4 days/week
Interview: Mandatory F2F interview at the client’s Jersey City, NJ location

Position Overview

We are seeking a Distinguished AI Engineer to provide top-tier individual-contributor technical leadership for an enterprise AI platform. This role will solve complex AI platform engineering challenges and build reusable, secure, reliable, observable, and cost-efficient capabilities that enable enterprise AI and GenAI solutions at scale.

This is a hands-on technical leadership role, focused on architecture, engineering, platform evolution, technical problem-solving, and influencing engineering teams rather than direct people management.

Key Responsibilities

  • Lead the design and engineering evolution of enterprise AI platform capabilities including AI gateways, model access and serving, model routing, RAG, AI agents, tool execution, orchestration, evaluation, observability, and LLMOps/MLOps.

  • Solve complex engineering trade-offs involving latency, throughput, resiliency, scalability, security, data isolation, portability, and cost.

  • Lead technical spikes, prototypes, reference implementations, deep design reviews, performance analysis, and production troubleshooting.

  • Establish engineering standards for availability, recovery, performance, capacity, telemetry, release safety, evaluation coverage, and inference cost.

  • Build reusable platform assets such as APIs, SDKs, Terraform/IaC modules, deployment patterns, CI/CD templates, dashboards, evaluation frameworks, and developer tooling.

  • Drive production excellence through observability, traceability, controlled releases, rollback strategies, incident learning, capacity planning, and cost optimization.

  • Implement AI security controls including IAM, authorization-aware retrieval, secure tool execution, prompt-injection defenses, data protection, logging, and auditability.

  • Partner with Cybersecurity, Risk, Compliance, Legal, Audit, Architecture, Product, and Business teams to translate enterprise requirements into practical technical controls.

  • Evaluate emerging AI technologies through hands-on technical assessments and determine adoption based on value, maturity, risk, operational fit, and total cost of ownership.

  • Mentor senior engineers and drive adoption of enterprise AI platform patterns across multiple engineering teams.

Required Qualifications

  • 10+ years of progressive experience in software engineering, distributed systems, cloud/platform engineering, AI/ML infrastructure, or related technical domains.

  • Proven experience building, scaling, transforming, or troubleshooting production platforms used by multiple engineering teams, products, or business domains.

  • Strong hands-on experience in several of the following:

    • LLM / Generative AI platforms

    • Model serving and inference

    • Inference optimization

    • AI gateways

    • Model routing

    • RAG

    • Embeddings / Vector Search

    • AI Agent frameworks

    • Tool execution / MCP

    • AI orchestration

    • LLMOps / MLOps

    • AI evaluation frameworks

    • AI observability

    • AI security / guardrails

  • Strong foundation in distributed systems, API/platform design, cloud-native architecture, containers, Kubernetes, networking, IAM, and secrets management.

  • Experience developing reusable engineering patterns, frameworks, APIs, infrastructure modules, CI/CD pipelines, or developer platforms.

  • Demonstrated ability to provide technical leadership across multiple teams without direct reporting responsibility.

Important: Candidates must be able to work onsite in Jersey City 4 days per week and attend a mandatory F2F interview at the client location.

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