Lead Agentic AI Engineer

Smart Soc Solutions; Bengaluru; On-site; INR 4,500,000 - 8,000,000; Full time

Job summary

Smart Soc Solutions in Bengaluru is seeking a Senior Agentic AI Developer with strong data engineering foundations to design, develop, and deploy autonomous AI agent systems for enterprise-scale use cases. The role blends agentic AI architectures with hands-on data pipelines, LLMs, and cloud platforms.

The candidate will architect and deliver multi-agent systems with planning, memory management, tool calling, and workflow orchestration, while integrating with enterprise systems and APIs.

Qualifications

• Proven experience designing and building agentic AI systems for enterprise use cases.
• Hands-on experience with ETL/ELT pipelines for structured and unstructured data.
• Experience with cloud platforms (Azure/AWS/GCP) and modern AI tooling.
• Strong Python and SQL skills, plus familiarity with data engineering workflows.

Responsibilities

• Architect and develop autonomous AI agents capable of executing complex business workflows with minimal human intervention.
• Design and maintain ETL/ELT pipelines that process structured and unstructured data at scale.
• Build single-agent and multi-agent systems with planning, reasoning, memory management, tool calling, and workflow orchestration.
• Integrate AI agents with enterprise systems, APIs, and third-party tools.
• Optimize AI applications for performance, scalability, latency, and cost.
• Implement agent evaluation, observability, and production monitoring.
• Apply prompting strategies to improve LLM-driven workflows.
• Implement Retrieval-Augmented Generation using semantic search and vector databases.
• Ensure LLM reliability with guardrails and AI safety best practices.
• Own full delivery lifecycle from concept to production.

Skills

Python

SQL

ETL/ELT

Data pipelines

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

OpenAI

Anthropic

Google Gemini

LLMs

RAG

Embeddings

Vector databases

Semantic search

AI safety

Guardrails

CI/CD

Git

Agile

Cloud platforms

Tools

Databricks

Snowflake

Azure

AWS

GCP

Job description

Job Description

We are seeking a Senior Agentic AI Developer with strong Data Engineering foundations to design, develop, and deploy autonomous AI agent systems for enterprise-scale use cases. The ideal candidate combines deep expertise in agentic AI architectures with hands-on experience in data pipelines, LLMs, and cloud platforms.

Role & responsibilities

• - Architect and develop autonomous AI agents capable of executing complex business workflows with minimal human intervention.


• - Design and maintain ETL/ELT pipelines that process structured and unstructured data at scale.


• - Build single-agent and multi-agent systems, incorporating planning, reasoning, memory management, tool/function calling, and workflow orchestration.


• - Integrate AI agents with enterprise systems, internal APIs, and third-party tools.


• - Optimize AI applications for performance, scalability, latency, and cost efficiency.


• - Implement agent evaluation frameworks, observability tooling, and production monitoring.


• - Apply Prompt Engineering, Prompt Optimization, and Prompt Chaining to improve LLM-driven workflows.


• - Implement Retrieval-Augmented Generation (RAG) patterns using semantic search, embeddings, and vector databases.


• - Ensure LLM reliability through guardrails, hallucination mitigation, and AI safety best practices.


• - Own the full delivery lifecycle: architect, develop, test, deploy, and maintain AI agent solutions from concept to production.


• - Collaborate with stakeholders across engineering, product, and business teams within Agile delivery frameworks.

Agentic AI & LLMs

• - Proven experience designing and building agentic AI systems for enterprise use cases.


• - Expertise in agentic frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or equivalent.


• - Hands-on experience building GenAI applications using OpenAI, Anthropic, Google Gemini, or open-source LLMs (Llama, Mistral, etc.).


• - Strong understanding of LLM concepts including RAG, embeddings, vector databases, and semantic search.


• - Knowledge of LLM evaluation, guardrails, and AI safety best practices.

Data Engineering

• - Strong proficiency in Python and SQL.


• - Solid experience designing and operating ETL/ELT pipelines for both structured and unstructured data.


• - Good to have - Hands-on experience with Databricks and/or Snowflake.

Infrastructure & Delivery

• - Experience with cloud platforms: Azure, AWS, or GCP.


• - Familiarity with Git, CI/CD pipelines, and Agile methodologies.


• - Strong problem-solving, communication, and stakeholder management skills.