As an AI Engineer – Agentic AI Systems, you will design, build, and ship intelligent agents and orchestration pipelines that power DOTMapper’s internal AI operating model. You will work within a focused AI team, reporting to the Senior Director of AI & Automation, to deliver agentic automation across marketing, operations, and data workflows.

You will be responsible for building the systems that directly impact how 400+ live client accounts across Australia are serviced.

This role requires a blend of AI/ML expertise, strong software engineering fundamentals, and a practical understanding of automation ecosystems.

KEY RESPONSIBILITIES

Agentic AI Development

- Design, develop, and deploy production-grade agentic AI systems using LLMs as the core reasoning layer.
- Build multi-agent orchestration architectures with structured tool routing via MCP (Model Context Protocol).
- Implement human-in-the-loop approval gates and automation maturity frameworks for safe agentic deployment.
- Develop and optimize Retrieval-Augmented Generation (RAG) architectures for domain-specific knowledge retrieval.
- Fine-tune prompts, agent workflows, and model interactions to improve accuracy, reliability, and performance.
- Evaluate and integrate emerging agentic AI frameworks and technologies into production workflows.

AI Automation & Workflow Engineering

- Build intelligent agents for marketing operations — paid media management, SEO automation, CRO, competitor intelligence, and performance reporting.
- Integrate LLMs with ad platform APIs (Google Ads, Meta, TikTok, LinkedIn), CRM systems (GoHighLevel), and data sources via REST APIs and event-driven patterns.




- Develop classification and routing logic for internal request intake, agent handoff, and task automation.

Software Engineering & Platform Development

- Develop scalable backend services and APIs using Python.
- Build production-ready AI Agents with robust architecture, security, and monitoring practices.
- Collaborate with cross-functional teams to ensure seamless deployment and integration of AI solutions.
- Optimize system performance, scalability, and reliability for AI workloads.

REQUIRED SKILLS & QUALIFICATIONS

Technical Skills

- 4–6 years of software engineering experience, with at least 3 years specifically in LLM/AI agent development in production.
- Strong proficiency in Python and/or JavaScript/TypeScript for Agentic AI and automation development.
- Deep hands-on experience with Generative AI, Large Language Models (LLMs), and agentic AI orchestration frameworks.
- Proven experience building multi-agent systems: multi-step reasoning loops, tool-calling agents, and human-in-the-loop workflows.
- Strong experience building RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases.
- Experience with prompt engineering, embeddings, vector databases, and AI agent frameworks.
- Knowledge of LLM platforms such as Anthropic Claude, OpenAI, Gemini, or similar ecosystems.




- Experience with workflow automation platforms such as n8n, Make, or similar.
- Hands-on experience with MCP (Model Context Protocol) — building or consuming MCP servers.
- Solid understanding of REST API patterns, webhooks, and event-driven architectures.
- Database proficiency: MySQL, MongoDB, PostgreSQL, and SQL databases.
- Familiarity with AI-assisted development tools such as Cursor and modern coding copilots.
- Understanding software engineering best practices: CI/CD, testing, and deployment.

Preferred Skills

- Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar agentic AI frameworks.
- Experience with ad platform APIs — Google Ads API, Meta Marketing API, or similar.
- Familiarity with CRM/marketing automation platforms such as GoHighLevel (GHL).
- Understanding digital marketing concepts — paid media, SEO, CRO, and campaign management.
- Prior experience working in a digital marketing
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Exposure to MLOps, model deployment, monitoring, and observability.

Pay: ₹600,000.00 - ₹800,000.00 per year

Advantages

- Provident Fund

Ability to commute/relocate:
- Bangalore City, Bengaluru, Karnataka: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):
- Do you have hands-on experience with RAG (Retrieval-Augmented Generation) systems?
- Which Agentic AI frameworks have you worked with hands-on?

Experience:
- AI/ML: 4 years (Required)
- Python: 3 years (Required)

Location:
- Bangalore City, Bengaluru, Karnataka (Preferred)

Work Location: In person

📌 AI Engineer (Bengaluru)
🏢 Dotmappers IT
📍 Bengaluru