Agentic AI System Architect - Python

About the Role :

As our Agentic System Architect, you will define and own the end-to-end architecture of our Python-based autonomous agent platform.

Leveraging cutting-edge frameworksLangChain, LangGraph, RAG pipelines, and moreyoull ensure our multi-agent workflows are resilient, scalable, and aligned with business objectives.

Key Responsibilities :

Architectural Strategy & Standards :

- Establish architectural patterns for chain-based vs. graph-based vs. retrieval-augmented workflows.

Component & Interface Design :

- Specify Python modules for LLM integration, RAG connectors (Haystack, LlamaIndex), vector store adapters, and policy engines.

- Design REST/gRPC and message-queue interfaces compatible with Kafka/RabbitMQ, Semantic Kernel, and external APIs.

Scalability & Reliability :

- Define fault-tolerance patterns (circuit breakers, retries, bulkheads) and lead chaos-testing of agent clusters.

Security & Governance :

- Implement governance : prompt auditing, model-version control, drift detection, and usage quotas.

Performance & Cost Optimization :

- Architect caching layers and GPU/CPU resource policies to minimize inference latency and cost.

Cross-Functional Leadership :

- Review and enforce best practices in Python code, CI/CD (GitHub Actions), and IaC (Terraform).

Documentation & Evangelism :

- Mentor engineers on agentic patternschain-of-thought, graph traversals, retrieval loopsand Python best practices.

Preferred Qualifications :

- Bachelors Degree in Computer Science, Information Technology, or related fields.

Preferred/Ideal Educational Qualification :

- Tech or M. Sc. Integrated M.Tech programs in AI/ML from top-tier institutions like IITs, IIIT-H, IISc.

Bonus or Value-Add Qualifications :

- LangChain, RAG architectures (DeepLearning.AI, Cohere, etc.

- Advanced Python (Coursera/edX/Springboard/NPTEL).

- Cloud-based ML operations (AWS/Azure/GCP).

Additional Skill Set :

- Experience building RAG pipelines with Haystack, LlamaIndex, or custom retrieval modules.

- Familiarity with vector databases (FAISS, Pinecone, Chroma) and knowledge-graph stores (Neo4j).

- Expertise in observability stacks (Prometheus, Grafana, OpenTelemetry).

- Background in LLM SDKs (OpenAI, Anthropic) and function-calling paradigms

Core Skills & Competencies :

- Python Mastery : Idiomatic Python, async/await, package management (Poetry/venv).

- Distributed Design : Microservices, agent clusters, RAG retrieval loops, event streams.

- Security-First : Embed authentication, authorization, and auditabilitys.

- Leadership : Communicate complex system designs clearly to both technical and non-technical stakeholders.

We are looking for someone with a proven track record in leveraging cuing-edge agentic frameworks and protocols.

This includes hands-on experience with technologies such as Agent-to-Agent (A2A) communication protocols, LangGraph, LangChain, CrewAI, and other similar multi-agent orchestration tools.

Your expertise will be crucial in transforming traditional, reactive AI applications into proactive, goal-driven intelligent agents that can signicantly enhance operational eciency, decision-making, and customer engagement in high-stakes domains.

We envision this role as instrumental in driving innovation, translating cuing-edge academic research into deployable solutions, and contributing to the development of robust, scalable, and ethical AI agentic systems.