Jobs

We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'. An AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.

This role is a mix of a few worlds coming together. You’ll be working with machine learning but not in a vacuum it’s applied to real engineering problems, working with 2D and 3D data from CAD, CAE, and CAM systems. A big part of the work is taking complex geometry, design workflows, and simulation data and figuring out how to turn that into something an AI system can actually understand and use.

We’re looking for someone who’s strong technically, especially in Python and ML, but also has the curiosity to dig into how things are designed and built in the real world. You might come from a research background or industry but either way you’re comfortable moving between theory and practical application. If you’ve spent time around mechanical systems or engineering design, that’s a big plus, because a lot of this role is about bridging that gap between advanced models and how engineers actually work day to day.

Responsibilities

Design, develop, and maintain geometry processing and simulation algorithms for engineering applications.
Build services for reading, processing, and writing 2D/3D engineering data.
Develop rendering modules for generating 2D/3D visual assets.
Curate and manage large-scale datasets for learning-based systems.
Implement and optimize post-training workflows for machine learning models.
Contribute to the development of domain-specific languages for engineering tasks.

What we are looking for

5+ years of academic or industry experience in one or more of the following areas: Geometric Processing, Simulation, Optimization, Machine Learning, or Domain-Specific Languages.
BSc or MSc in Compute

We are hiring senior engineers who build fast, think AI-first, and can take agentic AI from prototype to production. You will design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication. You will work primarily in Python for AI services and integrate with our enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure), delivering trustworthy, cost-efficient, low-latency experiences in real customer workflows.

What You'll Do!
Build agentic AI applications on Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.Design memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.Integrate via Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.Develop AI-native backend services in Python (FastAPI, asyncio) with evaluation harnesses, observability, and cost/latency/quality dashboards.Embed AI features into the MTech stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.Use AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.Implement safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.Implement full cycle agentic engineering: design → model/tool selecti

• *Title: Application Security (AppSec) + AI Engineering
• *Location: Iselin, NJ (Main) and other Cyber prime locations like Minneapolis, MN, Chander AZ, Dallas, TX (Los Colinas), Charlotte, NC
• *Duration: 6 Months Contract with Possible Ext.
• *Onsite Expectation: 3 days/week (Tuesday–Thursday)
• *JD:
• *Core focus:
• *Application Security (AppSec) + AI Engineering
• *Strong Application Security background

Hands-on with AppSec tools like:
• Checkmarx (critical)
• Other SAST/DAST tools

AI-driven Code Security & Remediation (production-level experience)
• Using AI to:
• Auto-generating secure code fixes
• Detect vulnerabilities
• Generate code remediation suggestions
• Integrating AI into security workflows

Tools / Platforms
• OpenAI (PRIMARY focus)
• GitHub Copilot
• Cloud-based AI coding tools

Real Use Cases Expected
• Deploying AI tools within AppSec pipelines
• Integrating AI with tools like Checkmarx
• Automating vulnerability remediation
• Improving developer productivity using AI

Required Tech Stack
• Python
• Exposure to TensorFlow / PyTorch
• Experience with:
• JIRA (tracking)
• Confluence (documentation)
• True Engineer background required

AppSec Tools and AI tooling
• Focus on AppSec AI eng. Deploying AI toolsto complement existing Appsec tools like Checkmarx and Black Duck
• experience in deploying AI tools for AppSec processes, including auto code remediation.
• The role requires experience with models like Copilot, OpenAI, and Entropic Cloud for code remediation.
• Candidates should have production experience implementing AI tools at scale, not just proof of concept (POC) code.
• The role is specific to AppSec AI engineering, not traditional AI engineering roles.
• role involves writing frameworks against AI models to remediate Checkmarx findings, not directly working with Checkmarx queries.
• various AI models.
• *--------
• *Thanks.
• *Regards,
• *Ashish
• *Email ID: ashish@Hireontech.com**

Luminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.

About LuminaryLuminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.

The RoleWe're looking for an LLM Engineer to architect our Physics AI Copilot—the next generation of intelligent assistants for engineering workflows. You'll work at the intersection of large language models and domain-specific engineering challenges, creating AI experiences that dramatically accelerate how engineers work.

ResponsibilitiesDevelop Agentic AI systems: Design and implement tools for agents to call; build reasoning, planning, and orchestration capabilities that enable the copilot to autonomously execute complex engineering workflows

Design and optimize RAG pipelines: Build retrieval-augmented generation systems over engineering documentation, physics simulation results, and domain knowledge bases

Implement memory and context management: Create persistent conversation memory and context systems that maintain coherent, l