Forward Deployed Engineer

Nirmata

$90K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years of experience in engineering or technical consulting
  • Bachelor's degree in Computer Science or related field
  • Deep expertise in Kubernetes and container management
  • Knowledge of AI and enterprise implementation techniques
  • Proficient in Linux OS administration and systems management

Responsibilities

  • Build solutions against live production systems to demonstrate provable ROI
  • Provide technical expertise in Kubernetes and Nirmata solutions for AI implementation
  • Verify and implement technical design solutions based on customer needs
  • Lead customer initiatives by architecting scalable solutions
  • Develop operational solutions for enterprise container adoption
  • Gather field insights and provide feedback to engineering teams
  • Manage technical escalations and document best practices for Nirmata solutions
  • Assist customers in capturing and documenting ROI and value

Benefits

  • Remote work opportunity within the USA/Canada
  • Access to a dynamic and innovative work environment
  • Opportunities for professional development and growth
  • Engagement in a live R&D loop impacting product evolution
  • Involvement in Fortune 500 client projects
Full Job Description
Forward Deployed Engineer, NIRMATA

As a Forward Deployed Engineer (FDE) at Nirmata, you will act as a critical bridge between our product velocity and the complex, real-world environments of our Fortune 500 customers. Unlike traditional roles, an FDE is embedded within the customer's ecosystem to ensure alignment of Nirmata's solution to key customer pain points, successful adoption of Nirmata's solution, delivering value and ROI realization.

You will be the single point of contact for all technical matters, providing leadership in architecting and operationalizing Nirmata's solution. This role is a live R&D loop; you will actively discover hidden workflow gaps and feed field insights back to our Engineering and Product teams to shape the future of the Nirmata platform.
Responsibilities
  • Custom Engineering & Proof of Value: Build working solutions against live production systems to demonstrate provable ROI and actual results tied to specific customer data and environments.
  • Cloud Native and AI Expert: With Kubernetes becoming the orchestrator of all software and AI, you will be an expert that goes deep in Kubernetes and Nirmata solutions to build and run AI as well as provide expertise to use Nirmata's AI solutions to customer problems.
  • Enterprise Implementation: Verify and implement detailed technical design solutions to address complex problems identified by customers, ensuring successful platform adoption.
  • Technical Leadership: Lead key customer initiatives by understanding business implications and architecting solutions that meet operational, integration, and scaling requirements.
  • Operational Excellence: Provide design and operational solutions for enterprise adoption of containers, including building necessary tools and automation.
  • R&D Feedback Loop: Gather field insights and provide clear, constructive product feedback to Nirmata Engineering teams based on real-world customer requirements.
  • Customer Advocacy: Manage technical escalations and educate customers with deep technical knowledge while documenting best practices for developing and deploying Nirmata solutions.
  • Value Realization: Assist customers in defining, capturing, and documenting the actual financial value and ROI provided by Nirmata.
Education and Experience
  • Experience: 4+ years of professional experience in engineering or technical consulting.
  • Education: Bachelor of Arts/Science or equivalent degree in Computer Science or a related area of study.
  • Location: Remote - USA/Canada.
Technical Expertise
  • Kubernetes Internals: Deep, hands-on experience with Kubernetes, containers, and container runtimes is mandatory. We are looking for candidates whose resumes prominently feature expertise in building and managing clusters.
  • AI: Knowledge of leveraging LLMs, (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques securely and optimally using LLMs within an Enterprise. Ability to implement agentic workflows incorporating
    Model Context Protocol (MCP), tool-calling, and OAuth-based authentication.

Cloud technologies: Knowledge and expertise in cloud technologies like virtualization, public clouds like AWS, and experience with tools for provisioning cloud resources like Terraform.
  • Systems Administration: Proficiency in Linux OS administration and management.
  • Infrastructure: Experience with internal development platforms, including standardizing and securing multi-tenant environments.
Knowledge and Skills
  • Communication: Strong communication skills are mandatory for presenting complex technical prognosis and impact to senior management.
  • Problem Solving: Ability to diagnose complex technical problems to their root cause in multi-technology environments.
  • Relationship Management: Essential customer relationship management and account planning skills to ensure alignment with customer priorities.
  • Consulting Mindset: Ability to adapt a consulting style appropriate to the situation and identify potential upsell opportunities during technical engagements.
  • Strategic Thinking: Ability to re-use existing experience to develop new solutions and shape technical strategies within the organization and for external customers.

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