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Mid-level experience, metro location, moderate brand, and niche GenAI platform skills increase competition to medium.
Core cloud and platform skills are transferable, but GenAI and vector DB expertise add moderate domain specificity.
Explicit 5-10 years requirement plus mandatory AWS, GenAI, and platform engineering skills makes shortlisting strict.
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Design, build, and operate a scalable Generative AI platform on AWS, focusing on model access, orchestration, security, and prompt lifecycle management.
Develop reusable capabilities for RAG pipelines, embeddings, agentic workflows, and implement scalable AWS infrastructure including Bedrock/agentcore services, compute, storage, and networking.
Support developers with integration, debugging, prompt tuning, cost optimization; develop rapid PoCs and implement observability for tracing, latency, token usage, and cost monitoring.
5-10 years of experience with a Bachelor’s/Master’s degree in Computer Science or related field.
Strong experience with AWS core services and networking (VPC, DNS, ALB).
Experience building GenAI systems using LLM APIs, RAG, or agent-based architectures.
Proficient in Python programming, API/microservices development; familiar with containers (Docker), Kubernetes, CI/CD pipelines; knowledge of AI orchestration frameworks and vector databases.
Work hours: 12 PM to 9 PM IST; relocation assistance available.
Hands-on engineer with a platform engineering mindset, able to deliver both quick PoCs and production-grade GenAI solutions on AWS.
Experienced in distributed systems and scalable architecture design, with knowledge of AI orchestration and multi-model strategies.
Able to collaborate across engineering, data, and product teams to maintain platform documentation, standards, and drive adoption of AI-assisted development tools.