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Zensar Technologies

AI Central - Senior AI Engineer

IndiaPosted today

Job description

Authoring repository-level context for AI coding agents: instruction files, skills, prompt libraries, and the conventions that make them consistent across many repositories.

  • Reading and reasoning about unfamiliar production code in at least two languages well enough to describe what it does and why.
  • Automated documentation and code-comprehension generation across legacy codebases.
  • Context and retrieval design: what to include, what to exclude, chunking and indexing, grounding agent output in real repository facts.
  • Strong technical writing for a developer audience, and the discipline to templatize rather than hand-craft each product.
  • Evidence of measurably improving agent output quality by improving context, not by changing the model.

Nice To Have

Exposure to legacy stacks — COBOL in particular — where added application and domain context is what makes agentic work viable.

  • AST, code-graph or static-analysis tooling used to generate context automatically.
  • Information architecture or taxonomy background.

Authoring repository-level context for AI coding agents: instruction files, skills, prompt libraries, and the conventions that make them consistent across many repositories.

  • Reading and reasoning about unfamiliar production code in at least two languages well enough to describe what it does and why.
  • Automated documentation and code-comprehension generation across legacy codebases.
  • Context and retrieval design: what to include, what to exclude, chunking and indexing, grounding agent output in real repository facts.
  • Strong technical writing for a developer audience, and the discipline to templatize rather than hand-craft each product.
  • Evidence of measurably improving agent output quality by improving context, not by changing the model.

Nice To Have

Exposure to legacy stacks — COBOL in particular — where added application and domain context is what makes agentic work viable.

  • AST, code-graph or static-analysis tooling used to generate context automatically.
  • Information architecture or taxonomy background.
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