Generative AI Engineer

1 week ago


New Delhi, India Recro Full time

Hiring: AI Architect (7+ yrs) — Agentic & GenAI SystemsLocation: Bengaluru / Gurugram |Full-time | AI Platforms & Architecture TeamAbout 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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