AI Engineer

Position: AI Engineer

• Experience 1–4 Years of Experience)

• Location: [BLR / Hybrid]

About the Role

We are looking for a highly proactive, self-motivated, and solution-oriented AI Workflow Engineer to join our team. This isn’t a passive execution role—we need a builder who requires minimal oversight, thinks critically about our current operational roadblocks, and can actively lead the charge in transforming our workflows, processes, and systems into an AI-first, agentic paradigm.

Because our core operations and primary client environment are deeply integrated with a major global search giant's ecosystem, you will be building solutions that interface smoothly with enterprise-grade cloud, data, and developer tooling. You will bring fresh perspectives, industry-proven patterns, and hands-on experience in modern AI tooling to help us level up our projects and reinvent how work gets done. If you love jumping into complex systems, identifying bottlenecks, and architecting autonomous or semi-autonomous multi-agent workflows, this role is for you.

Key Responsibilities

• Process Audit & Transformation: Analyze existing manual and semi-automated workflows to identify high-impact areas ripe for AI-driven transformation.

• Agentic Architecture Design: Design, build, and deploy multi-agent systems and pipelines using modern orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen, or custom agent loops) that can execute multi-step tasks autonomously.

• Ecosystem-Aligned Integration: Build workflows and leverage APIs that integrate cleanly within enterprise environments, utilizing cloud storage, serverless pipelines, and modern developer tooling.

• Proactive Innovation & Ideation: Bring ideas, architectural suggestions, and process improvements to the table to level up our engineering projects and internal operations.

• Continuous Optimization: Monitor agent performance, refine prompts, manage token usage/costs, evaluate guardrails, and optimize execution speed and accuracy across agentic loops.

Candidate Requirements

1. Experience & Background

• Technical Experience: 1 to 4 years of hands-on technical experience in software engineering, AI/ML engineering, or workflow automation.

• LLM Deployment: Demonstrated track record of building and deploying functional applications or automation pipelines leveraging Large Language Models (LLMs) (e.g., Gemini / Google Cloud AI APIs, OpenAI, Anthropic, or open-source models).

• Agentic Frameworks: Hands-on project experience with agentic frameworks or orchestration tools (e.g., LangChain, LangGraph, CrewAI, LlamaIndex, or AutoGen).

2. Mindset & Behavioral Traits (Non-Negotiable)

• Proactive Self-Starter: Highly motivated and autonomous; you thrive when given high-level objectives and take full ownership of figuring out the "how."

• Solution-Oriented: You view roadblocks as engineering puzzles and instinctively design smarter, automated alternatives.

• Idea Generator: You actively bring insights, suggest industry best practices, and challenge the status quo to elevate our team's capabilities.

3. Technical Stack & Skills

• Programming: Proficient in Python and familiarity with JavaScript/TypeScript/Rust where helpful.

• AI/ML & Cloud Tooling: Hands-on experience with prompt engineering, function calling / tool use, RAG (Retrieval-Augmented Generation), vector databases, and enterprise cloud ecosystems (Google Cloud / AWS / Azure).

• APIs & Integration: Experience building and consuming RESTful APIs, webhooks, and integrating third-party productivity tools (Slack, GitHub, Notion, databases, etc.) into agent ecosystems.

• Workflow Logic: Strong understanding of state management, error handling, and asynchronous programming required for reliable multi-agent loops.

What We Offer

• High Autonomy: Direct ownership over defining and shaping our agentic workflows with minimal bureaucracy.

• Frontier Tech: Opportunity to work directly at the frontier of AI agent orchestration within a top-tier enterprise ecosystem.

• Fast-Paced Growth: A culture that rewards proactive problem-solvers and fast execution.