AI Tooling Engineer

ZyteAI tooling

Workable workplace: remote; Workable locations: Bengaluru, Karnataka, IndiaFull-TimeMiddle

Salary not disclosed

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Job Details

Languages: Excellent written and spoken English, technical and non-technical.
Experience: 3+ years building and shipping production software, mostly in Python, with relational databases.
Required Skills: AWSPythonSQLGCPCI/CD

Have 3+ years of experience building and shipping production software, mostly in Python, with relational databases.
Have built and shipped at least one LangGraph agent used by real people, including tool calling, retrieval and embeddings, and prompt and context design.
Have hands-on experience with LLM APIs from major providers and cost and token optimisation.
Have hands-on experience with MCP or similar tool protocols, as both a server and a client.
Know how to evaluate AI systems using test sets, LLM-as-judge, and regression checks when prompts or models change.
Have experience with tracing and observability using Langfuse or a similar tool.
Have experience integrating SaaS APIs, SQL, and data warehouses.
Have cloud infrastructure experience with Google Cloud and/or AWS, including containers, managed databases, identity and access, and CI/CD.
Use AI coding agents every day and know how to check their output.
Understand security and permissions, including identity, least privilege, and restricting access appropriately.
Be comfortable with version control using GitHub or Bitbucket.
Have excellent written and spoken English for technical and non-technical communication.

Build the platform with the Principal Engineer in Tooling, delivering capabilities from design through production.
Connect internal systems and SaaS tools, including their APIs and data, to a shared model with appropriate access controls.
Build agents, the tools they use, MCP servers, and the context they need to answer well.
Own quality through evaluation sets, benchmarks, tracing, cost-per-answer tracking, and addressing user issues.
Turn proofs of concept into production internal tools in the cloud, with security and access controls.
Build with AI coding agents, using specifications, tests, and reviews to maintain code quality.
Contribute to company-wide AI tooling initiatives, including evaluating and standardising tools, tracking cost and usage, and setting standards for AI-built internal apps.
Talk with platform users across the company to identify what to build next and explain the work to technical and non-technical audiences.

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