15603 Agentic AI Architecture & Development

Cephas Consultancy Services Private Limited; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Cephas Consultancy Services Private Limited seeks an experienced AI Architect & Developer to lead agentic AI architecture and development in Bangalore. You will design and implement production-grade multi-agent systems, integrate LLMs, and optimize RAG pipelines within enterprise-scale backends.

The role requires hands-on Python, LangGraph experience, and strong knowledge of LangChain, AutoGen, and LLM data workflows. This is a full-time, on-site opportunity in Bengaluru.

Qualifications

• Bachelor's degree or equivalent in CS/Engineering/AI/ML.
• 7+ years of software engineering with enterprise AI/ML experience.
• Strong communication and ability to explain AI concepts.

Responsibilities

• Design and build production-grade multi-agent systems using LangGraph as the primary orchestration framework.
• Architect agent orchestration patterns including planning, tool use, persistent state management, memory, reflection, and multi-agent coordination.
• Develop and optimize RAG pipelines with document processing, chunking, embeddings, and vector DB integration.
• Build robust agent evaluation, testing, and observability frameworks for production reliability and performance.
• Design NLP-to-data query solutions integrating with Databricks Genie.

Skills

Python

LangGraph

LangChain

AutoGen

OpenAI API

FastAPI

Celery

Azure

CI/CD

Docker

Kubernetes

Education

Bachelor's degree in CS/Engineering/AI/ML or related field

Tools

Databricks Genie

Qdrant

Pinecone

Weaviate

ChromaDB

Job description

15603 Agentic AI Architecture & Development

About this position

https://talent.flowmingo.ai/jobs/MTU2MDMtYWdlbnRpYy1haS1hcmNoaXRlY3R1cmUtZGV2ZWxvcG1lbnQ

Positions:2 Full Time
Experience
7 - 11 Years

Agentic AI Architect & Developer

Location:Bangalore, Karnataka, India
Positions:2 Full Time
Experience:7 - 11 Years

Key Responsibilities:

Agentic AI Architecture & Development:

• Design and build production-grade multi-agent systems using LangGraph as the primary orchestration framework, with knowledge of LangChain, CrewAI, and AutoGen.
• Architect agent orchestration patterns including planning, tool use, persistent state management, memory, reflection, and multi-agent coordination.
• Develop and optimize RAG (Retrieval-Augmented Generation) pipelines with document processing, chunking strategies, embedding workflows, and vector database integration.
• Build robust agent evaluation, testing, and observability frameworks to ensure reliability and performance in production.
• Design natural language to data query solutions integrating with platforms such as Databricks Genie.

LLM Integration & Optimization:

• Integrate and manage LLM/SLM services (OpenAI, Azure OpenAI, Anthropic, open-source models) with appropriate model selection, prompt engineering, and cost optimization.
• Design prompt engineering strategies including chain-of-thought, few-shot, and structured output techniques for reliable agent behavior.
• Implement guardrails, safety mechanisms, and content filtering for AI-generated outputs.
• Evaluate and benchmark models for latency, accuracy, cost, and domain-specific performance.
• Build scalable Python backend services (FastAPI) that serve AI agent workflows to production applications at enterprise scale.
• Design and implement caching, rate limiting, persistent agent state, and conversation memory strategies.
• Develop event-driven microservices and real-time streaming for AI agent interactions.
• Develop APIs and integration layers that connect AI agents with enterprise data sources, tools, and external services.
• Implement distributed task processing (Celery) and event-driven autoscaling (KEDA) for production AI workloads.

Innovation & Technical Leadership:

• Stay current with the rapidly evolving Agentic AI landscape and evaluate emerging frameworks, models, and techniques.
• Lead proof-of-concept development for new AI capabilities, moving successful experiments to production.
• Mentor engineers on AI engineering best practices, prompt engineering, and agent design patterns.
• Contribute to technical documentation, architecture decision records, and AI solution design specifications.
• Champion the adoption of AI-powered development tools (Cursor AI, GitHub Copilot) across engineering teams.

Required Qualifications:

• Strong proficiency in Python with hands-on experience building production AI applications.
• Demonstrated experience with LangGraph or similar agentic AI frameworks (LangChain, CrewAI, AutoGen) for production systems.
• Hands-on experience with LLM API integration (OpenAI, Azure OpenAI, Anthropic) and prompt engineering.
• Experience designing and implementing RAG systems including embedding models, vector databases, and retrieval strategies.
• Solid understanding of multi-agent system design, agent orchestration, persistent state management, and memory patterns.
• Experience with Python web frameworks (FastAPI) and distributed task processing (Celery) for production APIs.
• Experience with event-driven microservices and real-time streaming patterns.
• Proficiency with AI-powered development tools (Cursor AI, GitHub Copilot, or similar) for AI-augmented software development across the SDLC.
• Proficiency with Git, CI/CD pipelines, and cloud platforms (preferably Azure).

Preferred Qualifications:

• Experience with vector databases (Qdrant, Pinecone, Weaviate, ChromaDB).
• Experience with Databricks Genie or similar natural language to data query platforms.
• Experience with AWS Bedrock AgentCore for managed agent runtime and multi-cloud agent deployment.
• Knowledge of model fine-tuning, quantization, and serving optimization.
• Experience with multi-tenant architecture patterns and enterprise-scale AI systems.
• Experience with containerization (Docker, Kubernetes) and event-driven autoscaling (KEDA).
• Understanding of AI safety, responsible AI principles, and enterprise governance requirements.
• Primary Framework:LangGraph (multi-agent orchestration with persistent state)
• Additional Frameworks:LangChain, CrewAI, AutoGen
• Techniques:RAG, prompt engineering, chain-of-thought, function calling, structured outputs
• Multi-Cloud:AWS Bedrock AgentCore (managed agent runtime)
• Patterns:Multi-agent orchestration, tool use, persistent state, memory management, agent evaluation

Experience & Qualifications:

• Bachelor's degree in Computer Science, Engineering, AI/ML, or a related technical field, or equivalent professional experience.
• 7+ years of proven software engineering experience with significant hands-on AI/ML work in enterprise environments.
• Strong communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
• Strong knowledge of Agile methodologies and principles.
• Demonstrated passion for staying current with the rapidly evolving AI landscape.