AI Automation Engineer

Beghou Consulting

AI Automation Engineer building AI-enabled consulting workflows for life sciences at Beghou. Collaborating to enhance automation and support internal AI initiatives in Bangalore.

Posted 7/22/2026full-timeBangalore • 🇮🇳 IndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building AI-enabled consulting workflows and integrating automation tools, with a strong foundation in full-stack engineering and hands-on experience with AI projects. Capable of rapid prototyping, documentation, and user support during rollout phases.

Highest-signal resume keywords

Python ProgrammingFull-Stack EngineeringAI Project DevelopmentAutomation Tool IntegrationLLM API Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaScriptAI AutomationRAG SystemsMCP ServersLLM-Powered ToolsPrototypingBug TriageUsability FixesDocumentation

Tools & Technologies

Claude CodeCodexCursorVS CodeN8nSharePointGitHubAzureZapierMake

Industry Keywords

AI Consulting WorkflowsDelivery AcceleratorsGovernance RulesInternal DeploymentUser Support

Tech Stack

Tools & technologies

AzureJavaScriptPython

About the role

Key responsibilities & impact

Build AI-enabled versions of consulting workflows using tools like Claude Code, Codex, Cursor, VS Code, n8n, Python, and modern agent frameworks (RAG, MCP servers, orchestration layers)
Prototype quickly — ship a first working version in days, then iterate tightly with the consulting team that will use it
Instrument automations so we can measure usage and quantified time saved
Own the technical end of 1–2 delivery accelerators each year, from first build through internal deployment
Integrate with Beghou systems (SharePoint, GitHub, Azure, approved LLM endpoints) under the governance rules set by the AI team
Document what you build — architecture, prompts, known limitations — so others can extend it
Support end users during early rollout (bug triage, usability fixes, minor feature additions)

Requirements

What you’ll need

2–5 years of combined experience across software engineering and AI/automation tinkering
Strong candidates often have a full-stack engineering background (Python, JavaScript, or similar) plus hands-on personal or professional AI projects
Demonstrable portfolio of AI projects — agents, RAG systems, automations, MCP servers, LLM-powered tools — whether professional or personal
Familiarity with at least one LLM at the API level (Claude, GPT, Gemini) and at least one automation tool (n8n, Zapier, Make, or custom Python)
MBA or equivalent business training is a plus but not required — build experience is valued over credentials

Benefits

Comp & perks

Competitive salary
Health insurance
Retirement plans
Flexible work arrangements
Professional development