Forward Deployed Engineer

Cashback24x7

India

Remote

INR 16,901,000 - 23,474,000

Full time

14 days+

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Benefits offered by this job

Health insurance
Paid time off
401(k) plan with company match
Remote-first workforce

Job summary

micro1 is hiring a Forward Deployed Engineer to directly partner with leading AI labs and enterprises. You will bridge research and production, shaping data pipelines, ML workflows, and agent-based systems.

The role spans ambiguous research questions, architecture, hands-on engineering, and partner-facing execution. You will build large-scale data intelligence systems, design taxonomies, and deploy end-to-end ML pipelines, working with researchers and enterprise stakeholders in a remote-first

Qualifications

  • Proficient Python developer with production-grade experience.
  • Ability to own end-to-end systems from research to deployment.
  • Experience working with large language models and multi-agent workflows.

Responsibilities

  • Define research goals and project direction with partners.
  • Build data intelligence systems for data collection, curation, and evaluation.
  • Develop ML pipelines for data preparation, training, evaluation, and experimentation.
  • Design data taxonomies and labeling frameworks for AI systems.
  • Create LLM applications including multi-agent systems and tool-using agents.
  • Collaborate with researchers and engineers to translate AI problems into scalable projects.
  • Develop infrastructure for model inference, experimentation, and deployment.

Skills

Python
Production systems
Ambiguous settings
Partner-facing execution

Tools

LLM tooling
Agent frameworks

Job description

Job Title: Forward Deployed Engineer

Job Type: Full-time

Location: Remote / Travel-required

The Role

We’re hiring a Forward Deployed Engineer to work directly with the world’s leading AI labs and enterprises as a technical research and implementation partner. This role sits at the intersection of applied AI, ML infrastructure, data intelligence, and partner-facing product development. You’ll help strategic partners define research directions, structure and curate high-quality data, implement ML and evaluation pipelines, and build the agentic systems that extend multi-turn agents and workflows in production. You should be comfortable moving between ambiguous research questions, technical architecture, hands‑on engineering, and partner-facing execution.

What You’ll Work On
  • Work directly with leading AI labs and enterprise partners to define research goals, technical requirements, and project direction.
  • Build large-scale data intelligence systems for collecting, organizing, evaluating, and improving training and evaluation data.
  • Implement ML pipelines for data curation, model training, evaluation, experimentation, and continuous improvement.
  • Design data taxonomies, labeling systems, and quality frameworks that improve dataset structure, model performance, and research outcomes.
  • Develop LLM applications, including multi-agent systems, tool-using agents, RAG workflows, evaluation harnesses, and human-in-the-loop systems.
  • Partner with research and engineering teams to translate ambiguous AI problems into scoped technical projects and production systems.
  • Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms.
  • Build systems that help partners move from one‑off AI experiments to reliable, repeatable, multi‑turn agent workflows.
  • Own systems across the full lifecycle, including discovery, architecture, implementation, deployment, reliability, iteration, and partner success.
What We’re Looking For
  • Able to operate independently in ambiguous, partner-facing settings with strong technical and product ownership.
  • Strong Python engineer with experience building and shipping production systems end to end.
  • Experience working with LLMs, agentic systems, multi-turn workflows, tool use, RAG, or AI automation.
  • Built or maintained data pipelines, ML infrastructure, evaluation systems, or research workflows.
  • Strong understanding of data quality, taxonomy design, labeling workflows, and dataset curation for AI systems.
  • Comfortable working directly with technical partners, researchers, founders, and enterprise stakeholders.
Preferred Qualifications
  • Background at a startup, AI infrastructure company, applied AI company, or research-focused engineering team.
  • Experience building systems for multi-turn agents, agent evaluation, workflow automation, or human‑in‑the‑loop AI.
  • Experience designing data taxonomies, annotation systems, evaluation rubrics, or dataset quality pipelines.
  • Experience acting as a technical partner to external customers, research teams, or strategic enterprise accounts.
  • Familiarity with modern LLM tooling, agent frameworks, model evaluation stacks, and ML experimentation platforms.
Compensation & Benefits

The national pay range for this full‑time position is base salary of $180,000 –$250,000 USD. All employees are eligible for equity compensation, and employees may also receive performance‑based bonuses, dependent on role and subject to company policies.

  • micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health‑insurance premiums
  • paid time off
  • a 401(K) plan with a company match
  • additional benefits designed to support a high‑performing, remote‑first workforce

micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to support@micro1.ai.

Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision‑making.

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