AI Engineer

Growthsphere.ai; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Growthsphere.ai in Bangalore seeks an experienced AI Engineer to build, fine-tune, and deploy agentic AI-driven financial applications. You will architect LLM-based agents, connect LLMs to data, and develop tools for complex tasks in finance.

The role emphasizes Python, LangChain/LangGraph, model fine-tuning, and GCP deployment across VertexAI services.

Qualifications

• 3–5 years hands-on experience building and shipping AI/ML applications.
• Strong Python skills and hands-on experience with agentic AI, LangChain/LangGraph, model fine-tuning, and GCP.
• A genuine drive to solve complex engineering problems and build production-grade AI solutions.
• Excellent problem-solving skills and attention to detail.
• Ability to work both independently and as part of a team.

Responsibilities

• Architect and implement LLM-based agents from the ground up, connecting state of the art LLMs to specialized data for enhanced accuracy.
• Develop custom tools to enable sophisticated AI solutions that can execute complex tasks in the financial domain.
• Implement interfaces for interacting with structured knowledge sources like ontologies.
• Work on multi-agent systems using tools like A2A and MCP.
• Own the deployment lifecycle, managing applications on GCP using services like GCE, GCS, and VertexAI.

Skills

Python

LangChain

LangGraph

LLM-based agents

Model fine-tuning

GCP

Tools

LangChain

LangGraph

VertexAI

GCE

GCS

Job description

Growthsphere is at the forefront of AI innovation, driving advancements in artificial intelligence and machine learning. We specialize in leveraging large language models (LLMs) to create cutting-edge applications that transform industries and empower businesses. Join our dynamic team and contribute to shaping the future of AI.

We're looking for an experienced AI Engineer in Bangalore who wants to build, fine-tune, and deploy agentic AI-driven financial applications.
You should have basic knowledge of LLM-based agents and LLM fine-tuning, and be strong in at least one of these areas. Financial experience is a bonus but not required.

LLM Agents:

You’ll architect and implement LLM-based agents from the ground up, connecting state of the art LLMs to specialized data for enhanced accuracy.

You’ll use LangChain/LangGraph and develop custom tools to build sophisticated AI solutions that can execute complex tasks in the financial domain.

You’ll implement interfaces for interacting with structured knowledge sources like ontologies.

You’ll work on multi-agent systems using tools like A2A and MCP.

LLM Fine-Tuning:

You’ll work on evaluating various LLMs on different capabilities, including creating interal evals.

You’ll work on fine-tuning state of the art LLMs on custom datasets to support our specific use cases, ranging from performing simple tasks to driving complex agents.

You’ll work on various types of fine-tuning, like CPT, SFT, and RL, using parameter efficient techniques like LoRA.

You’ll work with different LLM architectures (dense, MoE).

You will own the deployment lifecycle, managing your applications on GCP using services like GCE, GCS, and VertexAI.

Qualifications:

• 3-5 years of hands-on experience building and shipping AI/ML applications.
• Strong, practical skills in Python and demonstrable experience with agentic AI, LangChain/LangGraph, model fine-tuning, and GCP.
• A genuine drive to solve complex engineering problems and build production-grade AI solutions.
• Excellent problem-solving skills and attention to detail.
• Ability to work both independently and as part of a team.

If this sounds like the challenge you’ve been looking for,