AI Architect
A
AvahiAI and cloud
Source API remote eligibility restrictions: IndiaFull-TimeSenior
Salary5,000,000 INR per year
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Job Details
- Experience
- 8+ years of software engineering or cloud architecture experience, with 3+ years focused on AI/ML or generative AI solutions
- Required Skills
- AWSPython
Requirements
- Have 8+ years of software engineering or cloud architecture experience.
- Have 3+ years focused on AI/ML or generative AI solutions.
- Bring hands-on expertise with Amazon Bedrock, including model invocation APIs, Bedrock Agents, Knowledge Bases, and Guardrails.
- Have deep experience designing and operating Amazon OpenSearch Service clusters, including vector search (k-NN), index management, and relevance tuning.
- Have strong proficiency in Python.
- Have experience building and deploying RAG pipelines that integrate foundation models with enterprise data sources.
- Understand AWS networking, identity, and security services in the context of AI workloads.
- Have experience with multi-account AWS architectures, including AWS Organizations and Control Tower, and enterprise-scale deployments.
- AWS Certified Solutions Architect (Associate or Professional) is strongly preferred; AWS Certified Machine Learning – Specialty is a plus.
- Familiarity with LangChain, LlamaIndex, or equivalent orchestration frameworks is a plus.
Responsibilities
- Architect end-to-end AI/ML solutions using AWS Bedrock foundation models.
- Design multi-agent orchestration systems with Bedrock Agents, action groups, knowledge bases, and guardrails.
- Define embedding pipelines, vector indexing strategies, and retrieval patterns for RAG applications.
- Establish semantic and lexical search architectures with Amazon OpenSearch Service, including k-NN vector search and hybrid search.
- Design and implement scalable AWS cloud infrastructure and integrate Bedrock workflows with AWS data services and event-driven pipelines.
- Implement security practices for AI workloads, including VPC isolation, PrivateLink, KMS encryption, and fine-grained IAM policies.
- Drive infrastructure-as-code practices using AWS CDK, CloudFormation, or Terraform.
- Advise clients, lead AI proof-of-concept development, mentor development teams, and conduct architecture reviews.
- Define and track AI solution KPIs and produce technical documentation, runbooks, and client-facing deliverables.
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