Senior Agentic AI Backend Developer 

Job Description

Architecture & System Design :– Own and design complex distributed systems supporting AI agents, microservices, and asynchronous workflows.

– Evaluate architectural trade-offs for latency, reliability, cost, and scalability in AI-driven systems.

– Drive architecture decisions and influence platform-level design.

APIs, Data & Integrations :– Design and develop RESTful APIs and event-driven services to support agent orchestration.

– Work with SQL and NoSQL databases, vector databases, and caching layers to support high-performance AI workflows.

– Ensure seamless integration between AI services, core backend systems, and frontend applications.

Performance, Reliability & Security :– Identify and resolve performance bottlenecks in AI-enabled backend systems.

– Implement guardrails, fallback strategies, rate limiting, and monitoring for AI agents.

– Ensure security, compliance, and data integrity across services.

Collaboration & Leadership :– Collaborate closely with product managers, data scientists, ML engineers, and frontend teams.

– Review code, mentor SDE-1/SDE-2 engineers, and promote engineering best practices.

– Own systems or services end-to-end with a strong sense of accountability.

Key Result Areas :

Education :

– Bachelors degree in Computer Science, Engineering, or a related field (Masters degree is a plus).

Experience :

– 4.5+ years of backend engineering experience.

– Hands-on experience building production-grade backend systems.

– Practical experience with Agentic AI or Generative AI systems is highly preferred.

TECHNICAL SKILLS :

Backend & Systems :– Proficiency in Python, Go, Java, or Node.js.

– Strong experience with REST APIs, microservices architecture, and asynchronous systems.

– Experience with Docker, Kubernetes, and container-based deployments.

Agentic AI & GenAI (Must / Strong Plus) :– Experience building or integrating AI agents / autonomous systems.

– Familiarity with LLM frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.

– Experience with RAG pipelines, embeddings, and vector databases (FAISS, Pinecone, Chroma, Weaviate).

– Understanding of tool calling, plannerexecutor patterns, and agent orchestration.

– Exposure to LLM evaluation, prompt/version management, and observability.

Data & DevOps :– Strong understanding of SQL and NoSQL databases.

– Experience with CI/CD pipelines, monitoring, and system observability.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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