AI Engineer (AWS Bedrock & Agentic AI)
Durapid Technologies Pvt Ltd · Bangalore Urban
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Jul 20, 2026
Bangalore Urban
Jul 22, 2026
What this job asks for AI summary
This role centres on building and deploying production-ready AI applications on AWS, with a focus on agent-based systems, RAG pipelines, and LLM integration using AWS Bedrock. Day-to-day work includes designing multi-agent workflows, developing serverless architectures with Lambda and Step Functions, and creating secure REST APIs. It suits an experienced Python developer with a solid background in enterprise AI and cloud-based generative AI solutions.
Senior level · 5+ years
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The title 'AI Engineer' carries no explicit seniority level, so advertised seniority is Unspecified. The 5–7+ years requirement and enterprise-grade scope support a Senior classification.
The '5–7+ years' range is mapped to the overall years minimum of 5 (the lower bound of the stated range).
Agent-Based AI Systems is listed as a mandatory skill but names no specific tool or framework; it is captured through the concrete technologies that implement it (AWS Bedrock, LangChain/LangGraph/CrewAI/AutoGen, etc.) rather than as a standalone skill entry, per the guideline against emitting generic concepts.
Prompt engineering and AI workflow orchestration are listed under Mandatory Skills but name no specific technology, so they are omitted per the guideline against generic concepts.
Vector database options (Pinecone, OpenSearch, Weaviate, FAISS, ChromaDB) appear under Preferred Skills; Pinecone is used as the primary name with the others as alternatives since they are interchangeable for the same function.
MLOps appears under Preferred Skills but names no specific tool, so it is omitted.
Read the full posting
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