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Mid-level Bangalore AI role with broad LLM and dev-tooling requirements increases applicant density.
Skills in LLM APIs, Python, and developer tooling are highly transferable across industries.
Explicit 3+ years, 2+ years LLM experience, and mandatory tech stack enforce strict filtering.
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Lead end-to-end AI initiatives from pilot to production, building scalable AI tools for defect analysis, test automation, and performance engineering used across multiple client implementations.
Develop and integrate LLM-based agentic workflows and AI tooling into development and QA processes, enhancing automation layers and supporting developer workflows with code review and test generation tools.
Productionize AI prototypes into hardened services with monitoring and reporting, while driving AI governance and collaborating cross-functionally with QA, engineering, and leadership teams.
3+ years of hands-on software engineering experience with production code delivery.
At least 2 years of practical experience building with LLM APIs (Anthropic/Claude, OpenAI, or similar), including prompt engineering, agentic pipelines, and RAG.
Proficiency in Python and/or JavaScript/TypeScript (Node.js), plus experience with test automation frameworks (Playwright, Selenium) and CI/test infrastructure.
Experience building developer-facing tooling within the software development lifecycle (SDLC), familiarity with Jira/Confluence, and working with structured project data at scale.
Experience working directly within complex development teams, understanding SDLC workflows to build effective automation and AI tooling that integrates into developer and QA routines.
Ability to scope ambiguous business problems into fast prototypes and production-quality AI solutions that have measurable impact across client projects.
Familiarity with AI orchestration frameworks (e.g., MCP), enterprise AI platforms, and collaboration with cross-functional teams managing live client implementations.