Gen AI Lead

We are looking for a Generative AI Tech Lead and Developers to provide technical leadership and architectural direction for building and operating production-grade GenAI solutions on AWS. This role combines hands-on development, solution architecture, team mentorship, and operational ownership. Team will own end-to-end delivery of GenAI platforms using Python, AWS Bedrock (Agent Core SDK), AWS Strands SDK, and modern DevOps and observability practices, ensuring scalability, security, reliability, and cost efficiency. Solid understanding of LLMs(Anthropic (Claude LLM)), embeddings, prompts, tokens, latency, cost factors Practical experience with RAG architectures, vector stores, and grounding strategies Ability to select and justify model choices (open-source vs proprietary) Experience supporting real-world use cases, not just POCs or demos Experience in AWS bedrock platform using Python, Strands SDK Multi-Agents, LangGraph/CrewAI

Key Responsibilities Generative AI Development Design and implement

Generative AI applications

using

AWS Bedrock , including: o

Bedrock Agent Core SDK o

Foundation Models (FM) integration oPrompt engineering and agent orchestration Build AI workflows using

AWS Strands SDK

for scalable model execution and orchestration Develop and maintain reusable

AI components, APIs, and services

in Python Optimize model performance, latency, and cost for production workloads

AWS-Native Application Development Design and develop

cloud-native applications

on AWS using: o

AWS Lambda, ECS/EKS, EC2 o

API Gateway / Application Load Balancer o

S3, DynamoDB, Aurora, OpenSearch Implement secure IAM roles and policies aligned with least-privilege principles Build event-driven and microservices-based architectures

DevOps & CI/CD Design and maintain

CI/CD pipelines

using tools such as: AWS CodePipeline / CodeBuild / CodeDeploy o

GitHub Actions / GitLab CI (as applicable) Infrastructure as Code (IaC) using: AWS CloudFormation / CDK / Terraform Automate build, test, deployment, and rollbacks for GenAI workloads

Observability & Operations Implement end-to-end

observability

for AI and application workloads: Amazon CloudWatch (logs, metrics, alarms) o

AWS X-Ray tracing o

Custom metrics for model behavior and performance Monitor: Model response latency o

Token usage and cost o

Error rates and failure scenarios Participate in

incident management , root cause analysis, and system optimization

Security, Governance & Compliance Ensure secure handling of data used in AI workflows Implement: Encryption at rest and in transit o

Secure secrets management (AWS Secrets Manager / Parameter Store) Follow enterprise standards for: Data privacy o

AI governance o

Responsible AI usage

Required Skills & Qualifications Technical Skills (Must Have)

• Python

(advanced proficiency) Hands-on experience with: o

AWS Bedrock o

AWS Bedrock Agent Core SDK o

AWS Strands SDK Strong knowledge of

AWS services

and cloud-native design patterns Experience building and deploying applications

natively on AWS CI/CD pipeline implementation and maintenance Observability and monitoring in production environments

Preferred Skills (Good to Have) Experience with: LLMs, RAG (Retrieval Augmented Generation) Vector databases and embeddings Knowledge of containerization: Docker, Kubernetes (EKS) Familiarity with MLOps or Model Lifecycle Management Experience with cost optimization for AI workloads Understanding of ethical AI and responsible AI principles

Please share resume prannoyk1@birlasoft.com with Details:

Current CTC: Expected CTC: Notice period: Total Gen Ai Exp: AWS Bedrock Exp: SDK/ Agen Rock Exp: Python Engineering Exp: