Artificial Intelligence Engineer

Growthsphere Ai

Bengaluru

Hybrid

INR 2,800,000 - 4,200,000

Full time

2 days ago
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Job summary

Growthsphere Ai in Bengaluru is seeking an experienced AI Engineer to build LLM-powered applications and agentic workflows. You will fine-tune models, implement function-calling, and develop scalable Python systems on GCP, leveraging LangChain/LangGraph for multi-step agents.

Responsibilities include designing NLP algorithms, building retrieval-augmented generation pipelines, and ensuring production-grade AI solutions with robust monitoring and tooling.

Qualifications

  • Bachelors/Masters degree in CS, Engineering, Data Science, or related fields.
  • 3-7 years of AI/ML experience with LLMs and agent frameworks.
  • Strong Python skills; experience with LangChain, LangGraph, Pydantic, and async tooling.
  • Hands-on GCP experience deploying production AI workloads.
  • Understanding of ML fundamentals, embeddings, vector databases, and retrieval systems.
  • Experience with function calling, API integrations, and RAG pipelines.
  • Strong problem-solving skills and attention to detail.
  • Ability to work independently and in collaborative environments.

Responsibilities

  • Design, develop, and deploy AI-driven applications utilizing large language models.
  • Implement and optimize NLP algorithms and AI functionalities.
  • Create autonomous agents capable of planning, tool-use, and multi-step decision flows.
  • Integrate LangChain/LangGraph to build robust agent workflows and memory-backed systems.
  • Implement routing, evaluation loops, and agent monitoring.
  • Develop and maintain function-calling mechanisms and APIs for external systems.
  • Write clean, scalable Python for AI/ML applications with modern libraries.
  • Deploy AI workloads on GCP using Compute Engine, Cloud Storage, Cloud Functions, Vertex AI.
  • Build and maintain RAG pipelines with embeddings and vector stores; optimize retrieval quality.
  • Collaborate with cross-functional teams and communicate progress to stakeholders.

Skills

Python programming
LLM experience
Agent frameworks
NLP algorithms
Independent work

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

LangChain
LangGraph
Pydantic
Async tooling
Docker
Kubernetes
Playwright
BeautifulSoup
Vertex AI

Job description

Job Summary: We are seeking an experienced AI Engineer with hands‑on expertise in building LLM-powered applications and agentic workflows using models such as GPT, Claude, Llama, and other frontier models. The ideal candidate will have experience fine‑tuning LLMs, using LangChain/LangGraph for multi‑step agents, implementing function‑calling, developing robust Python applications, and building scalable systems on GCP. Experience in RAG architectures, data science, and production‑grade AI systems is essential.

Key Responsibilities:
Develop and Deploy AI Applications:
  • Design, develop, and deploy AI-driven applications utilizing large language models like GPT, Llama, and Claude.
  • Implement and optimize algorithms for natural language processing (NLP) tasks and other AI-related functionalities.
  • Create autonomous and semi-autonomous agents capable of planning, tool-use, and multi-step decision flows.
Utilize LangChain/LangGraph:
  • Integrate LangChain and LangGraph to build robust agent workflows, tool orchestration, and memory-backed systems.
  • Implement advanced capabilities like routing, evaluation loops, and agent monitoring.
Function Calling and API Integration:
  • Develop and maintain function-calling mechanisms for seamless integration with other services and applications.
  • Create and manage APIs to facilitate communication between AI models and external systems.
Python Development:
  • Write clean, efficient, and scalable code in Python for AI and machine learning applications.
  • Use modern Python libraries (Pydantic, async frameworks, orchestration tools) to build reliable systems.
GCP Cloud Services:
  • Deploy and manage AI and machine learning applications on Google Cloud Platform (GCP) infrastructure.
  • Utilize GCP services such as Compute Engine, Cloud Storage, Cloud Functions, and Vertex AI for model training, deployment, and storage.
Data Science and Machine Learning:
  • Apply core ML and data science methods to improve model performance and system reliability.
  • Build and maintain large-scale scraping and ingestion pipelines using Playwright, BeautifulSoup, etc.
  • Retrieval-Augmented Generation (RAG) Systems:
  • Architect, optimize, and maintain RAG pipelines combining vector stores, embeddings, and hybrid search.
  • Improve retrieval quality, latency, filtering, and contextual relevance.
Agentic Systems:
  • Build multi-tool, multi-step agent workflows capable of autonomous reasoning, planning, and execution.
  • Improve agent reliability through evaluation, guardrails, and structured output enforcement.
  • Collaboration and Communication:
  • Collaborate with cross-functional teams to understand requirements and deliver AI solutions.
  • Communicate technical concepts and project progress to stakeholders effectively.
Qualifications:
  • Bachelors/Masters degree in CS, Engineering, Data Science, or related fields.
  • 3-7 years of experience in AI/ML, with strong exposure to LLMs and agent frameworks.
  • Strong Python skills; experience with LangChain, LangGraph, Pydantic, and async tooling.
  • Hands‑on GCP experience, including deploying production AI workloads.
  • Understanding of ML fundamentals, embeddings, vector databases, and retrieval systems.
  • Experience with function calling, API integrations, and RAG pipelines.
  • Strong problem‑solving skills and attention to detail.
  • Ability to work independently and in collaborative environments.
Preferred Skills:
  • Familiarity with multi‑modal models and fine‑tuning methods (LoRA, adapters).
  • Knowledge of MLOps and model monitoring practices.
  • Experience with containerization (Docker, Kubernetes).
  • Strong documentation, experimentation, and evaluation skills.
  • Experience with scraping frameworks like Playwright.
  • Building or utilizing ontologies with AI systems.
  • Experience with Databricks.
  • Understanding of finance related concepts.
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