Job Description - Ai Engineer

About the role-

Tristone is embedding agentic AI
directly into its workflows and systems. As a member of the Agentic AI
engineering team, you'll help build agents, MCP servers, and evaluation loops
that make AI-generated code reliable, auditable, and fast to ship. You'll work
closely with senior members of Tristone to deliver pragmatic, high-impact AI
integrations at scale.

 
Key Responsibilities-

  • Contributing to the platform by implementing agents, MCP servers,
    and supporting services that propose and apply changes to large codebases

  • Assisting in developing retrieval systems that give AI agents and
    developers accurate, up-to-date context from large codebases and design
    artifacts

  • Helping measure and improve AI-generated changes by building
    compile/test/evaluate pipelines (static analysis, style and safety checks,
    performance gates, code review)

  • Applying Tristone’s best practices in concurrency, telemetry,
    configuration hygiene, and performance-sensitive code paths to ensure AI
    outputs are reliable and idiomatic

  • Collaborating with colleagues on experiments to evaluate and
    improve AI-driven workflows

  • Complying with IT policies and procedures.
  • Maintaining security of information at all times.
Requirements-

  • 1+ years of experience
  • Proficiency in a high-level
    programming language (Java or Python preferred)

  • Experience contributing to
    developer-facing or production systems

  • Curiosity and eagerness to learn
    about AI/LLM application patterns, even if you haven't worked closely with
    them yet

  • Strong communication skills;
    comfortable working with engineers in a fast, collaborative environment

Strong
preferred-

  • Exposure to AI tools or workflows
    (e.g., LangChain, LangGraph, AutoGen, or similar)

  • Experience with retrieval systems
    (vector search, embeddings, or hybrid approaches)

  • Familiarity with compiler/static
    analysis or large-scale refactoring tools

  • Interest in customizing or
    fine-tuning open-weight models

  • Knowledge of model-serving or
    evaluation infrastructure

Qualification-

 

  • BS+ in Computer Science (or related)
    with strong fundamentals (algorithms, data structures, systems)



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