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Mid-level AI automation role in Bangalore with desirable LLM skills increases applicant competition.
AI engineering and automation skills transfer easily across industries despite life-sciences domain knowledge.
Explicit 2–5 years requirement plus mandatory LLM and automation tooling raises selection strictness.
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Develop and deploy AI-enabled automation of existing consulting workflows for life sciences, delivering operational AI tools that are adopted and save hours.
Rapidly prototype, iterate, and maintain 1–2 AI automation delivery accelerators annually from build through deployment and early user support.
Integrate solutions with internal systems (SharePoint, GitHub, Azure, approved LLMs) while documenting architecture, prompts, and limitations for maintainability.
2–5 years combined software engineering and AI/automation experience, including building AI projects like agents, RAG systems, or LLM-powered tools.
Proficiency with Python or JavaScript/TypeScript, APIs, version control, and deploying software.
Experience using at least one LLM API (e.g., Claude, GPT, Gemini) and one automation tool (e.g., n8n, Zapier, Make, or custom Python).
Work Experience Required: 2–5 years software engineering plus AI/automation projects. Notice period: Not explicitly mentioned in the JD.
An AI-native engineer comfortable building AI agents and automations from idea to working prototype rapidly with iterative improvements.
Experienced full-stack engineer with a demonstrated portfolio of AI projects and practical understanding of consulting workflows.
Adaptable to ambiguous problem statements, able to collaborate closely with business users to tailor solutions without full specs.