Applications Engineers, Agentic Workflows

Backend Engineer · Mid · Full Time · Remote

Remote (United States) · RemoteUSD 156k – 180k3mo ago
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Role

What you'll do.

Rescale seeks an Application Engineer specializing in Agentic Workflows to build and deploy AI-driven automation across engineering and CAE workflows. This customer-facing, product-first role combines deep software engineering expertise with hands-on experience integrating intelligent agents into complex engineering tools, simulation data pipelines, and end-to-end orchestration systems. You'll transform early-stage agent prototypes into production-grade, reusable platform capabilities while working directly with engineering customers to encode real workflows into deterministic, hardened automation systems.

Responsibilities

  • Design and Deploy Agent-Driven Automation: Build and ship agent-based capabilities that operate across engineering and CAE workflows, designing agents that interact intelligently with engineering tools, simulation data, and complex processes while ensuring reliability and repeatability in production environments.
  • Architect Workflow Automation Systems: Encode engineering workflows as structured, agent-executable steps with clearly defined inputs, outputs, and guardrails. Integrate agents into end-to-end pipelines as reusable, production-grade components rather than one-off scripts or point solutions.
  • Harden and Productionize Agent Use Cases: Transform early-stage agent prototypes into deterministic, production-ready systems through rigorous testing, debugging, and optimization across agent logic, tool execution, data handling, and orchestration layers.
  • Direct Customer Engagement and Field Deployment: Work directly with customer engineers to understand real workflows, technical constraints, and operational requirements. Participate in on-site technical working sessions and critical deployment milestones, with occasional travel for execution-focused engagements.
  • Debug Complex Multi-Layer Systems: Identify and resolve issues spanning agent decision logic, tool execution, data pipelines, and orchestration frameworks. Develop diagnostic expertise across the entire automation stack to ensure system reliability and performance.
  • Translate Customer Learnings into Product Direction: Close gaps between real-world workflows and platform capabilities by gathering concrete customer feedback and technical insights. Feed operational learnings back into product teams to inform platform evolution and feature prioritization.

Qualifications

What we look for.

Technical

  • Python Proficiency

    Strong expertise in Python with ability to write robust, maintainable code for automation systems, API integration, and data processing pipelines. Must be comfortable with Python's ecosystem for building production systems.

  • Agent-Based and LLM Systems Experience

    Hands-on experience building, deploying, or operating agent-based systems or LLM-driven applications. Understanding of agent frameworks, reasoning loops, tool use patterns, and agentic workflow orchestration is essential.

  • Engineering Software Automation

    Demonstrated experience building automation around engineering or technical software, including CAE tools, simulation platforms, and solver-driven processes. Knowledge of engineering workflows and technical computing pipelines is critical.

  • Workflow Orchestration and Tool Integration

    Experience orchestrating complex tools, scripts, and workflows across multiple systems. Proficiency in designing deterministic, reliable automation that handles tool execution, data transformation, and inter-system communication.

  • Data Handling and Simulation Workflows

    Familiarity with CAE workflows, simulation data structures, solver-driven processes, and computational data pipelines. Understanding of how simulation data flows through engineering tools and systems.

Education

  • Bachelor's Degree in Computer Science, Software Engineering, or Related Field

    Formal education in computer science, software engineering, physics, mechanical engineering, or related quantitative field. Equivalent professional experience demonstrating strong engineering fundamentals is acceptable.

Experience

  • Software Engineering Foundation

    Minimum 3-5 years of professional software engineering experience with strong fundamentals in system design, debugging, and production software development. Track record of shipping reliable, scalable systems.

  • Internal Tool to Product Conversion

    Prior experience converting internal automation or one-off scripts into reusable, product-grade components. Understanding of the transition from prototype to production and the considerations involved.

  • Engineering Domain Knowledge

    Background working with engineering teams, technical computing, or scientific software. Direct experience in aerospace, energy, manufacturing, or life sciences domains is highly valuable but not required.

Skills

Required

  • Python

    Production-level Python expertise for building automation systems, API clients, and data pipelines.

  • Agent Framework Architecture

    Understanding of agent frameworks, including ReAct patterns, tool-use systems, agentic orchestration, and LLM integration patterns.

  • System Debugging and Troubleshooting

    Strong capability to debug across multiple layers including agent logic, API interactions, data transformations, and distributed system components.

  • API Integration

    Experience integrating with external systems and APIs, building API clients, and handling authentication, error handling, and data serialization.

  • Software Architecture Fundamentals

    Understanding of system design principles, modularity, testability, and creating reusable components from monolithic scripts.

Preferred

  • LLM Prompt Engineering

    Nice to have

    Experience with prompt design, few-shot learning, and tuning LLM behavior for specific tasks and domains.

  • CAE and Simulation Tools

    Nice to have

    Familiarity with specific CAE platforms such as ANSYS, ABAQUS, OpenFOAM, or similar engineering simulation software.

  • Container and Orchestration Technologies

    Nice to have

    Knowledge of Docker, Kubernetes, or similar containerization and orchestration platforms for deployment automation.

  • Data Engineering and ETL

    Nice to have

    Experience building data pipelines, ETL processes, or handling large-scale data transformation relevant to engineering datasets.

  • Machine Learning Operations

    Nice to have

    Familiarity with MLOps practices, model deployment, monitoring, and operational considerations for AI systems in production.

  • Aerospace, Energy, or Manufacturing Domain Experience

    Nice to have

    Professional experience in aerospace, energy, manufacturing, or life sciences sectors provides valuable domain context.

Tech stack

Languages

PythonJavaScript/TypeScript

Frameworks

LangChain or LlamaIndexFastAPIPydantic

Databases

PostgreSQLVector Databases (e.g., Pinecone, Weaviate)

Tools

Git and Version ControlDockerKubernetesJupyter Notebooks

Other

OpenAI API or Similar LLM ProvidersRESTful APIs and gRPCHPC and Cloud Computing PlatformsCI/CD Pipelines

Compensation

Pay and benefits.

Base·USD 156,000 – 180,000

Equity·Stock options

Benefits

  • Comprehensive Health Insurance

    Medical, dental, and vision coverage for employees and eligible dependents, with competitive company contribution rates.

  • Equity and Stock Options

    Participate in company growth through stock option grants aligned with your role level and tenure.

  • Professional Development

    Learning and development budget for courses, conferences, certifications, and professional growth in AI, engineering, and software systems.

  • Flexible Work Environment

    Hybrid or remote-friendly work arrangements with flexibility to support both focused deep work and collaborative engineering.

  • Unlimited PTO

    Flexible time-off policy allowing you to manage work-life balance and take time for rest and personal development.

  • Collaborative Mission-Driven Culture

    Work with passionate engineers and researchers focused on transforming digital engineering and scientific discovery across industries.

  • Impact at Scale

    Direct influence on how engineering organizations adopt agent-driven automation and shape core platform capabilities used across aerospace, energy, life sciences, and manufacturing.

Process

Interview steps.

  1. 01

    Initial Screening Call

    30-45 minute conversation with technical recruiter to discuss your background, interest in agent-based systems, and experience with engineering software automation.

  2. 02

    Technical Assessment

    Take-home or live coding exercise focusing on Python proficiency, system design thinking, and practical problem-solving around workflow automation or agent integration challenges.

  3. 03

    Engineering Interview

    Deep-dive technical conversation with engineering team members covering agent architecture, debugging strategies, and how you approach turning prototypes into production systems.

  4. 04

    Product and Customer Context Interview

    Discussion with product or customer-facing team to assess your ability to translate customer needs into technical solutions and provide feedback on platform direction.

  5. 05

    Leadership and Culture Fit

    Final conversation with engineering leadership to evaluate collaboration style, ability to operate autonomously on field deployments, and alignment with Rescale's mission.

Full posting

Original listing.

About Rescale

Rescale is pioneering the future of engineering and scientific discovery. As the leader in digital engineering, we’re transforming how products are developed—through intelligent automation, applied AI, data management, and the integration of the world’s largest network of engineering and R&D applications. Joining Rescale means becoming part of a diverse, collaborative, and mission-driven team that’s unlocking faster innovation across industries like aerospace, energy, life sciences, and manufacturing. We’re solving complex challenges that traditional HPC can’t—and we’re seeking passionate, curious minds to help build the next wave of breakthroughs

We are seeking a highly motivated Application Engineer, Agentic Workflows to help build and deliver the next generation of AI Physics capabilities at Rescale!

You will work directly with platform and AI teams to design and ship agent-based capabilities that operate on real engineering tools and data. You will also work closely with customers to apply these agents to real workflows, ensuring what gets built is reliable, repeatable, and productizable.

The role is customer-facing, but product-first. Work done in customer environments must translate into reusable product capabilities rather than one-off solutions.

This role is ideal for engineers who enjoy building real systems, integrating with complex engineering software, and turning early agent prototypes into durable platform capabilities.

What You’ll Do

  • Build and ship agent-driven automation across engineering and CAE workflows

  • Design and implement agents that interact with engineering tools, simulation data, and workflows

  • Encode engineering workflows as structured, agent-executable steps with clear inputs, outputs, and guardrails

  • Integrate agents into end-to-end pipelines as reusable capabilities rather than one-off scripts

  • Harden early agent use cases into deterministic, production-ready systems

  • Debug and resolve issues across agent logic, tool execution, data handling, and orchestration

  • Work directly with customer engineers to understand real workflows and technical constraints

  • Close gaps between real workflows and platform capabilities, feeding concrete learnings back into product direction

  • Operate as a builder first, with the ability to be forward-deployed on critical engagements when needed

Core Skill Set

  • Strong software engineering fundamentals, with heavy emphasis on Python

  • Hands-on experience building automation around engineering or technical software

  • Familiarity with CAE workflows, simulation data, and solver-driven processes

  • Experience building or deploying agent-based or LLM-driven systems

  • Experience orchestrating tools, scripts, or workflows across multiple systems

  • Ability to design deterministic, reliable automation around complex tools

  • Experience turning internal automation into reusable, product-grade components

  • Comfortable debugging across tool execution, data handling, and orchestration layers

Customer Engagement & Travel

This role includes direct customer engagement during agent deployments and early workflow rollouts. Expect occasional travel to customer sites for deep technical working sessions or critical milestones. Travel is execution-focused and tied to building and deploying real capabilities.

Why This Role Matters

AI Agent Applications Engineers ensure that agent-based automation is not just experimental, but reliable, usable, and embedded into real engineering workflows.

Your work will directly influence how engineering organizations adopt agent-driven automation, and will shape the core capabilities that become part of the platform.

Rescale is an equal opportunities employer and welcomes applications from all qualified persons regardless of their race, sex, disability, religion/belief, sexual orientation or age. As part of our standard hiring process for new employees, employment with Rescale will be contingent upon successful completion of a comprehensive background check. Here at Rescale, we are committed to being transparent in our policies around candidate privacy. For more details on the information Rescale collects in your application, please view the Rescale Applicant Privacy Policy here.

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