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AI Agent Engineer

Roles & Responsibilities

  • Earned a Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, or a related field.
  • 5+ years of experience in software engineering, platform engineering, or related roles.
  • Proven expertise in AI model building and agent development; strong background in ML and LLM-driven systems.
  • Experience with compound AI systems, vector databases, and tool-calling AIs; excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.

Requirements:

  • Design and build complex multi-step AI agent pipelines around open- and closed-source LLMs, including tool-calling hierarchies.
  • Develop tools enabling AIs to interact with critical enterprise software platforms while aligning AI designs with business objectives and industry best practices.
  • Create data generation and processing pipelines to train and fine-tune custom ML models, and implement and manage training and evaluation pipelines for LLMs.
  • Manage AI infrastructure across cloud platforms (AWS, Azure, GCP) and deploy inference endpoints as part of the core product infrastructure.

Job description

Job Summary

As we build to the next level, we’re looking for a top-quality AI engineer with a strong focus on AI agents - someone who knows how to leverage LLMs, both open-source and closed, in combination with complex tool-calling hierarchies and operational patterns.

This is an opportunity to build scalable, secure, and high-impact AI technologies for the future of enterprise. If you thrive in high-growth, fast-moving environments and are passionate about AI, ML, and AI agents, we want to hear from you.

Key Responsibilities

1. AI Agent Building (60%)

  • Develop complex multi-step agentic pipelines around open- and closed-source LLMs.

  • Build tools enabling AIs to interact with critical enterprise software platforms.

  • Ensure AI designs align with business objectives and industry best practices.​

2. ML development and fine-tuning (30%)

  • Create data generation and processing pipelines to train and fine-tune custom ML models.

  • Implement and manage training and evaluation pipelines for LLMs.

3. Deployment and AI Systems Infrastructure (10%)

  • Manage AI infrastructure across platforms such as AWS, Azure, or GCP.​

  • Deploy inference endpoints and serve AI and LLM technologies as part of our core product infrastructure.

Required Qualifications

  • Earned a Bachelor’s degree, Master's degree or Ph.D. in Computer Science, Engineering, or a related field.​

  • 5+ years of experience in software engineering, platform engineering, or related roles.​

  • Proven expertise in AI model building and agent development.

  • Strong background in ML and LLM-driven systems development.

  • Experience with compound AI systems, vector databases, and tool-calling AIs.

  • Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.​

Preferred Qualifications

  • Experience building & deploying production-grade, large-scale AI applications.

  • Familiarity with AI deployment, evaluation, and monitoring practices.

  • Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.​

Join the Future of AI at Tessera Labs

We're looking for someone who enjoys building reliable, scalable systems that help teams move faster. If you take pride in cutting-edge AI, value clear ownership, and want to have a meaningful impact in a fast-moving environment, you’ll fit right in.

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