Generative AI Engineer

RecroBengaluru, Karnataka, India

30+ days ago

Job description

🧠 Hiring : AI Architect (7+ yrs) — Agentic & GenAI Systems

📍 Location : Bengaluru / Gurugram | 💼 Full-time | AI Platforms & Architecture Team

🚀 About the Role

We’re looking for an AI Architect with a strong engineering background and proven expertise in Agentic Frameworks and Generative AI platforms .
You’ll own the design and scale of production-grade agentic systems , ensuring they’re secure, observable, and optimized for performance and cost on AWS.
This role demands a hands-on architect — someone who can debug code, model infrastructure, and lead developers through deep technical challenges.

⚙️ What You’ll Do

Architect and scale Agentic AI systems (planning, reasoning, and tool-calling) and GenAI / RAG pipelines .

Design production architectures on AWS (EKS, Bedrock, S3, SQS / SNS) with a focus on cost, performance, and reliability.

Implement and optimize multi-agent frameworks such as Semantic Kernel, LangGraph, AutoGen, or CrewAI .

Build retrieval and hybrid search pipelines with grounding, caching, and hallucination control.

Drive observability via OpenTelemetry + Datadog (metrics, tracing, SLIs / SLOs).

Set security, compliance, and data-governance standards for GenAI deployments.

Mentor engineers, conduct design reviews, and lead technical architecture discussions.

🎯 What We’re Looking For

7–10 years in software / AI engineering with at least 4+ years in GenAI applications .

Agentic framework experience is mandatory (Semantic Kernel, LangGraph, AutoGen, or CrewAI).

Expert in Python (3.11+), FastAPI, asyncio, profiling, and pytest .

Proven experience in architecting GenAI / RAG systems using AWS Bedrock , OpenSearch Serverless, or equivalent.

Deep understanding of AWS cloud services , distributed systems, and observability.

Passion for building reliable, secure, and high-performing AI platforms at scale.

🌟 Bonus Points

Expertise in multi-agent orchestration and reasoning flows.

Hands-on experience with vector databases (Pinecone, Redis, pgvector).

Familiarity with evaluation frameworks , rollout gates, and FinOps optimization.

Exposure to policy-as-code (OPA) , feature management (LaunchDarkly) , or NeMo Guardrails .

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Generative Ai Engineer • Bengaluru, Karnataka, India

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