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Sr Architect

Actively Reviewing the Applications

Birlasoft

India Full-Time
Posted 17 hours ago • Apply by June 11, 2026

Job Description

Area(s) of responsibility

Key Responsibilities

GenAI & Agentic AI Architecture

  • Architect end-to-end GenAI-first and Agentic AI solutions on AWS using:
    • Amazon Bedrock
    • Amazon AgentCore
    • Strands SDK Multi-Agents
    • AWS Agents for Bedrock
    • Knowledge Bases for Bedrock
    • Guardrails for Bedrock
    • Amazon SageMaker for model lifecycle & fine‑tuning
  • Design multi-agent systems supporting planning, reasoning, tool invocation, memory stores, and multi-step workflows.
  • Develop high-performance RAG architectures using:
    • Amazon OpenSearch Serverless
    • Kendra
    • Aurora + pgvector
    • Redis Enterprise
  • Implement secure prompt flows, tool integrations, embeddings pipelines, and evaluation frameworks optimized for AWS.
  • Build Python-based microservices (FastAPI/Django) integrated with AWS AI stack.
  • Design scalable architectures using AWS-native components:
    • Lambda, Step Functions, EventBridge, SQS, DynamoDB, API Gateway, ECS/EKS
  • Implement enterprise-class LLMOps using:
    • Amazon SageMaker Pipelines
    • AWS CodePipeline / CodeBuild
    • CloudWatch / X-Ray observability
  • Establish standards for:
    • Agent governance & safety
    • Secure model invocation
    • Guardrails & content filters
    • Latency & cost optimization patterns
    • Ensure compliance with enterprise security standards using:
      • IAM, KMS, VPC endpoints, PrivateLink, CloudTrail
    • Optimize AI workloads for cost, performance, and scalability, including model caching, selective batching, and autoscaling strategies.
    • Conduct architecture reviews, threat modeling, and performance benchmarking.
    • Assess new AWS AI services, foundation models, agent frameworks, and vector DBs.
    • Create internal accelerators, reusable patterns, and AWS-focused reference architectures for:
      • Multi-agent orchestration
      • RAG 2.0 / context enrichment
      • Federated retrieval
      • Enterprise tool integration
    • Lead PoCs, prototypes, and technical spikes to validate emerging AWS GenAI capabilities.
    • Mentor engineering teams on AWS GenAI patterns, LLMOps, cloud-native development, and distributed AI architectures.
    • Provide technical direction, best practices, and deep architectural guidance across delivery teams.
    • Create internal documentation, architecture blueprints, and engineering playbooks.
    Required Skills & Qualifications

    • AWS Certified Associate/Professional Solutions Architect.

    Required Skills

    Django FastAPI Python AWS Prototyping Redis DynamoDB IAM RAG Cloud native VPC Adobe Illustrator LLMOps OpenSearch Threat modeling Amazon Bedrock Amazon CloudWatch Amazon EventBridge Amazon EKS API Gateway Observability Generative AI Auto Scaling Agentic AI Serverless AWS CodeBuild AWS Step Functions
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